Re: 활성산소, Nitro oxidative stress 바이오 마커....

[문형철]

ROS

RNS

redox signaling and redox biology

redox balance - ROS 과잉

oxidative stress & nitro oxidative stress

oxidants

antioxidants

Br J Pharmacol. 2017 Jun; 174(12): 1771–1783.

Published online 2017 Mar 6. doi: 10.1111/bph.13673

PMCID: PMC5446576

PMID: 27864827

Biomarkers of oxidative and nitro‐oxidative stress: conventional and novel approaches

Ana Cipak Gasparovic, 1 Neven Zarkovic, 1 Kamelija Zarkovic, 2 Khrystyna Semen, 3 Danylo Kaminskyy, 4 Olha Yelisyeyeva, 5 and Serge P. Bottari

 6 , 7

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Abstract

The concept of oxidative stress (OS) that connects altered redox biology with various diseases was introduced 30 years ago and has generated intensive research over the past two decades. Whereas it is now commonly accepted that macromolecule oxidation in response to ROS is associated with a variety of pathologies, the emergence of NO as a key regulator of redox signalling has led to the discovery of the pathophysiological significance of reactive nitrogen species (RNS).

RNS can elicit various modifications of macromolecules and lead to nitrative or nitro‐OS. In order to investigate oxidative and nitro‐OS in human and in live animal models, circulating biomarker assays have been developed. This article provides an overview of key biomarkers used to assess lipid peroxidation and NO/NO2 signalling, thereby stressing the necessity to analyse several OS biomarkers in relation to the overall (aerobic) metabolism and health condition of patients. In addition, the potential interest of heart rate variability as the non‐invasive integrative biomarker of OS is discussed.

산화 환원 생물학의 변화와 다양한 질병을 연결하는 

산화 스트레스(OS)의 개념은 

30년 전에 도입되어 지난 20년 동안 집중적인 연구를 불러일으켰습니다. 

ROS에 반응하는 

거대 분자 산화가 다양한 병리와 관련이 있다는 것은 

이제 일반적으로 받아들여지고 있지만, 

산화 환원 신호의 핵심 조절자로서 

NO가 등장하면서 

반응성 질소 종(RNS)의 병리 생리학적 중요성이 발견되었습니다. 

RNS는 

거대 분자의 다양한 변형을 유도하여 

질산염 또는 니트로-OS를 유발할 수 있습니다. 

인간과 살아있는 동물 모델에서 

산화성 및 니트로-OS를 조사하기 위해 

순환 바이오마커 분석법이 개발되었습니다. 

이 글에서는 

지질 과산화 및 NO/NO2 신호를 평가하는 데 사용되는 

주요 바이오마커에 대한 개요를 제공하여 

환자의 전반적인 (유산소성) 신진대사 및 건강 상태와 관련하여 

여러 OS 바이오마커를 분석할 필요성을 강조합니다. 

또한

OS의 비침습적 통합 바이오마커로서

심박수 변동성의 잠재적 관심에 대해 논의합니다.

Linked Articles

This article is part of a themed section on Redox Biology and Oxidative Stress in Health and Disease. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v174.12/issuetoc

Abbreviations4‐HNEtrans‐4‐hydroxy‐2‐nonenalACRacroleinALEadvanced lipoxidation end‐productsDNP2,4‐dinitrophenylhydrazineFRRfree radical reactionHRVheart rate variabilityLOlipid alkoxyl radicalLOOlipid peroxyl radicalLOOHlipid hydroperoxideLPOlipid peroxidationMDAmalondialdehydeNO+nitrosonium ionNrf2Nuclear factor (erythroid‐derived 2)‐like 2OMPoxidatively modified proteinOSoxidative stressPUFApolyunsaturated fatty acidsRNSreactive nitrogen speciesTBARSthiobarbituric acid reactive substancesUPRunfolded protein response

Table of Links

LIGANDS

4‐HNE, 4‐hydroxy‐2‐nonenal

NO, nitric oxide

Nrf2

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This Table lists key ligands in this article which are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY (Southan et al., 2016).

Introduction

Oxidative stress (OS), which was first introduced as a concept in redox biology and medicine in 1985 by Helmut Sies and Enrique Cadenas (Cadenas and Sies, 1985; Sies and Cadenas, 1985), has gained increasing interest over the years to become a major field of investigation in chemistry, life sciences and medicine.

This concept connects oxidative chemistry with biological stress responses. However, it has the disadvantage of concealing redox chemistry, which plays a key role in cell homeostasis and signalling and in physiology, which is, for a large part, dependent on both oxidation and reduction reactions (Frein et al., 2005). This complex field of biochemistry, which plays a key role in the regulation of a variety of enzymes involved in essential signalling pathways, is now referred to as ‘redox signalling’ (Ullrich and Kissner, 2006) (Figure 1).

소개

1985년 헬무트 시에스와 엔리케 카데나스가

산화 환원 생물학 및 의학의 개념으로 처음 도입한

산화 스트레스(OS)는

수년에 걸쳐 화학, 생명 과학 및 의학의 주요 연구 분야가 될 정도로

관심이 높아졌습니다(Cadenas and Sies, 1985; Sies and Cadenas, 1985).

알데히드, 하이드로퍼옥사이드 및 퀴논의 대사적 역할은 산소 자유 라디칼과 관련된 산화 전이에 중점을 두고 효소 활동과 관련하여 조사되었습니다. 알데히드의 산화 대사(에탄올 산화, 모노아민 산화효소 활성 또는 지질 과산화 중 지질 하이드로퍼옥사이드의 산화적 분해에서 비롯됨)는 알칸 생성 및 저수준 화학 발광의 원천입니다. 두 파라미터 모두 세포 산화 조건을 반영하므로 알데히드 산화 효소 활성의 부산물이 알데히드의 초기 효소 산화와 화학 발광 및 알칸 생성으로 이어지는 산화 종의 발생 사이의 연결 고리에 관여할 수 있다고 추론할 수 있습니다. 과산화수소의 대사는 두 가지 측면에서 고려되었습니다. 첫째, 글루타치온 퍼옥시다아제 유사 활성과 항산화 활성을 나타내는 셀레노르 유기 화합물 PZ-51에 의해 매개되는 해독 메커니즘의 틀 내에서 과산화수소 환원; 둘째, 강력한 산화 등가물인 단일 분자 산소의 원천으로서 효소 촉매에 의한 과산화수소의 불균형화. 항암제와 같은 치료제에 사용되는 퀴논의 세포 독성은 슈퍼옥사이드 라디칼과 그에 따른 더 많은 활성 산소 종의 형성으로 인한 산화 스트레스와 관련이 있는 것으로 여겨집니다. 효소 촉매에 의한 메나디온의 1전자 환원은 퀴논의 2전자 환원과는 달리 세포 독성 효과의 발생에 상당한 역할을 하는 것으로 보입니다. 1전자 환원 과정을 선호하거나 2전자 환원 과정을 감소시키는 조건에서 저수준 화학발광을 관찰한 것은 퀴논 대사 및 관련 세포 독성 효과의 변화를 모니터링하는 데 저수준 화학발광 측정의 실용성을 나타냅니다.

이 개념은

산화 화학을 생물학적 스트레스 반응과 연결합니다.

그러나

세포 항상성과 신호 전달에 핵심적인 역할을 하는 산화 환원 화학,

그리고 대부분 산화 및 환원 반응에 의존하는

생리학을 숨긴다는 단점이 있습니다(Frein et al., 2005).

필수 신호 전달 경로에 관여하는

다양한 효소의 조절에 핵심적인 역할을 하는

이 복잡한 생화학 분야를 현재 '산화 환원 신호 전달 redox signalling '이라고 부릅니다(Ullrich and Kissner, 2006)(그림 1).

Figure 1

Nitro‐oxidative status with respect to relative NO and O2 .‐ fluxes.

Another aspect that is often neglected when addressing O2·‐ is the role of NO, which is the primary substrate of the original ROS, the superoxide anion O2 −. Indeed, the reaction rate of ·NO with O2 −, estimated at 9 × 109 mol−1·s−1, is 3 – 4 times faster than its catalysis by Cu,Zn‐SOD (2.4 × 109 mol−1·s−1) and 2 to 4 orders of magnitude faster than its reaction with macromolecules such as aminoacids (≈ 106–107 mol−1·s−1), proteins (≈ 5 × 106 mol−1·s−1 for albumin), lipids (≈ 106 mol−1·s−1 for palmitate) and DNA (≈ 5 × 105 mol−1·s−1)(Frein et al., 2005; Thomas, 2015; Thomas et al., 2015). This reaction gives rise to peroxynitrite (ONOO−), which is a highly reactive nitrogen species (RNS), producing nitration and nitrosation of substrates, often proteins that play important pathophysiological roles (Ullrich and Kissner, 2006; Schulz et al., 2008; Bottari, 2015). Besides triggering nitration and nitrosation, ONOO−, which is also a strong oxidant, can also induce DNA deamination and oxidation (deRojas‐Walker et al., 1995), methionine sulfoxidation (Swaim and Pizzo, 1988), zinc finger oxidation (Crow et al., 1995) and lipid oxidation and peroxidation (Trujillo and Radi, 2002). ONOO− has also been reported to oxidize glutathione thereby leading to glutathiolation of selected cysteine residues (Viner et al., 1999).

Under physiological conditions, NO concentrations are usually nanomolar and therefore serve as a ‘sink’ for the picomolar concentrations of superoxide, thereby preventing oxidative mechanisms. Under certain pathophysiological conditions, superoxide and NO concentrations rise, and nitrosative and nitrative stress almost always precede OS (Daiber et al., 2002; Wayenberg et al., 2011). OS usually occurs when O2 − fluxes result in equimolar or higher concentrations than those of NO. Hence, some authors have suggested that ‘OS’ should rather be called ‘nitro‐OS’ (Wayenberg et al., 2011; Kossmann et al., 2014). As indicated previously, S‐nitrosation and nitration as well as glutathiolation play an important role in physiological cell homeostasis and can therefore also be considered as redox signalling mechanisms. OS and nitro‐OS that have negative outcomes should in our view only be used in pathological conditions.

Because nitro‐OS is involved in a large variety of disorders encompassing most chronic conditions, for example, neurological, cardiovascular, respiratory, inflammatory or neoplastic diseases, as well as some acute diseases such as infection, hypoglycaemia, hypoxia, ischaemia or toxic shock, it is of primary interest to be able not only to detect it, but also to follow its evolution in order to monitor the effectiveness of treatments. Whereas assays for more than 70 biomarkers have been developed to study ‘OS’ (Woolley et al., 2013), very few have yet been proposed and validated for nitrosative and nitrative stress (Chen et al., 2014; Mikhed et al., 2016). As OS biomarkers have been extensively reviewed recently by Frijhoff et al. (Frijhoff et al., 2015), this review will focus on some particular aspects of biomarkers of redox signalling, OS and of nitro‐OS.

O2--를 다룰 때 종종 무시되는 또 다른 측면은

원래 ROS의 주요 기질인 슈퍼옥사이드 음이온 O2 -인

NO의 역할입니다.

Another aspect that is often neglected when addressing O2·‐ is the role of NO, which is the primary substrate of the original ROS, the superoxide anion O2 −

https://www.sciencedirect.com/science/article/pii/S2213231715000452

산화질소 (-NO , 일산화질소)는 다양한 생리적 및 병리학적 상태와 관련된 가장 독특한 생물학적 신호 전달 분자 중 하나입니다. 산화질소의 다양한 역할을 제대로 이해하기 위해서는 기본적인 생화학적 특성을 이해하는 것이 필수적입니다. 스테로이드나 단백질과 같은 대부분의 신호 전달 효과 분자는 고전적인 수용체-리간드 상호작용을 통해 상당한 수명과 기능을 갖습니다. -그러나 -NO는 생물학적 조건에서 금속 및 기타 자유 라디칼이라는 두 가지 유형의 분자와만 반응하는 수명이 짧은 자유 라디칼 기체입니다. 이러한 단순한 상호작용은 무수히 많은 복잡한 중간체를 생성할 수 있으며, 이 중간체들은 각각 고유한 표현형 효과를 가지고 있습니다. 이러한 이유로 다양한 실험 환경에서 결과를 비교할 때 -NO에 대한 반응이 무작위로 나타나거나 모순되는 경우가 많습니다. 이 글에서는 -NO 대사에 중점을 두고 -NO 신호를 결정하는 화학적, 생물학적, 미세 환경적 요인에 대해 간략하게 설명합니다. 산소(산소, O2 )가 -NO 대사에서 수행하는 중요한 역할과 -NO의 생물학적 효과에 미치는 영향에 대해 중점적으로 설명합니다. 이 정보와 이러한 개념은 학생과 연구자가 -NO의 생물학적 효과를 규명하는 실험의 데이터 해석에 대해 생각할 수 있도록 돕기 위한 것입니다.

실제로,

-NO와 O2 -의 반응 속도는

9 × 109 mol-1-s-1로 추정되며,

Cu,Zn-SOD에 의한 촉매 작용보다

3~4배 빠릅니다(2. 4 × 109 mol-1-s-1),

아미노산(≈ 106-107 mol-1-s-1),

단백질(알부민의 경우 ≈ 5 × 106 mol-1-s-1),

지질(팔미테이트의 경우 ≈ 106 mol-1-s-1) 및

DNA(≈ 5 × 105 mol-1-s-1)와 같은 거대 분자와의 반응보다

2~4배 빠릅니다(Frein et al, 2005; 토마스, 2015; 토마스 외, 2015).

이 반응은

반응성이 높은 질소 종(RNS)인

퍼옥시니트라이트(ONOO-)를 생성하여

기질, 종종 중요한 병리 생리학적 역할을 하는

단백질의 질화 및 질소화를 생성합니다(Ullrich and Kissner, 2006; Schulz et al., 2008; Bottari, 2015).

 nitration and nitrosation,

질화 및 질소화를 유발하는 것 외에도

강력한 산화제인 ONOO-는

DNA 탈아미네이션 및 산화(deRojas-Walker 등, 1995),

메티오닌 설폭산화(Swaim and Pizzo, 1988),

아연 손가락 산화 zinc finger oxidation (Crow 등, 1995) 및

지질 산화 및 과산화(Trujillo and Radi, 2002)를 유발할 수 있습니다.

Besides triggering nitration and nitrosation, ONOO−, which is also a strong oxidant, can also induce DNA deamination and oxidation (deRojas‐Walker et al., 1995), methionine sulfoxidation (Swaim and Pizzo, 1988), zinc finger oxidation (Crow et al., 1995) and lipid oxidation and peroxidation (Trujillo and Radi, 2002). ONOO− has also been reported to oxidize glutathione thereby leading to glutathiolation of selected cysteine residues (Viner et al., 1999).

ONOO-는

또한 글루타티온을 산화시켜

선택된 시스테인 잔류물의 글루타티올화를 유도하는 것으로 보고되었습니다(Viner et al., 1999).

생리적 조건에서

NO 농도는 일반적으로 나노몰이므로

피코몰 농도의 슈퍼옥사이드에 대한

'싱크' 역할을 하여 산화 메커니즘을 방지합니다.

특정 병리 생리학적 조건에서는

과산화물과 NO 농도가 상승하고,

질산화 및 질산성 스트레스가

거의 항상 OS에 선행합니다(Daiber et al., 2002; Wayenberg et al., 2011).

OS는

일반적으로 O2 - 플럭스가

NO 농도와 같거나 더 높은 농도가 될 때 발생합니다.

따라서 일부 저자는 'OS'를 오히려 '니트로-OS'라고 부르자고 제안했습니다(Wayenberg et al., 2011; Kossmann et al., 2014).

앞서 언급한 바와 같이

S-질산화와 질산화,

글루타티올화는

생리적 세포 항상성에 중요한 역할을 하므로

산화 환원 신호 전달 메커니즘으로 간주할 수도 있습니다.

부정적인 결과를 초래하는

OS와 니트로-OS는 병리학적 조건에서만 사용해야 한다고 생각합니다.

니트로-OS는

감염, 저혈당, 저산소증, 허혈, 독성 쇼크와 같은

일부 급성 질환뿐만 아니라

신경계, 심혈관, 호흡기, 염증 또는 종양 질환 등

대부분의 만성 질환을 포괄하는

매우 다양한 질환에 관여하므로

이를 감지할 수 있을 뿐만 아니라

치료 효과를 모니터링하기 위해

그 진화를 추적하는 것이 주요 관심사입니다.

'OS'를 연구하기 위해

70개 이상의 바이오마커에 대한 분석법이 개발되었지만(Woolley et al., 2013),

아직 질산화 및 질산염 스트레스에 대해 제안되고 검증된 분석법은 거의 없습니다(Chen et al., 2014; Mikhed et al., 2016).

OS 바이오마커는

최근 Frijhoff 등에 의해 광범위하게 검토되었으므로(Frijhoff 등, 2015),

이 리뷰에서는 산화 환원 신호,

OS 및 니트로-OS의 바이오마커의 특정 측면에 초점을 맞출 것입니다.

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Biomarkers of S‐nitrosation and of nitration

The main RNS in eukaryotes are ONOO−, dinitrogen trioxide (N2O3) and probably the elusive nitrosonium ion (NO+). As elegantly demonstrated by Daiber and Ullrich (Daiber et al., 2002), the posttranslational modifications elicited by RNS depend on the relative fluxes of NO and O2 −. Briefly, as long as the NO concentration remains threefold higher than the O2 − concentration, NO reacts with the generated ONOO− to yield N2O3 which, possibly through the formation of NO+, causes S‐nitrosation (RSNO) of certain cysteine residues. This modification, which may be called nitrosative stress if associated with a cellular dysfunction, is rapidly reversible by reduction and therefore depends on the redox status of the biological system. When the O2 − flux increases further such that its concentration approaches or reaches that of NO, the availability of NO is no longer enough to allow the generation of N2O3 and the major RNS are now ONOO− and NO2· ONOO− is responsible for the nitration (R‐NO2) of selected tyrosine residues and NO2· is a potent oxidant. Tyrosine nitration is a covalent modification which probably requires an enzymatic activity to be reversed. It is referred to as nitrative stress if it is associated with altered functions.

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Detection of S‐nitrosation

As indicated above, S‐nitrosation is a readily reversible process, which is highly dependent upon the redox status. Moreover, S‐nitrosothiols are inherently unstable as the RSNO bond dissociation energy is only 23 to 32 kcal·mol−1. One of the major problems when trying to assess nitrosative stress or even the potential S‐nitrosation of a cysteine residue in a biological sample is the serious risk of artefactual generation or reversal, during sample preparation. This risk is further increased by the biotin‐switch technique (Jaffrey et al., 2001), which is currently used to label the S‐nitrosated cysteines in order to make them detectable. Indeed, the many steps involved, increase the risk of RSNO hydrolysis and the lack of specificity of the nitrosocysteine reduction step by ascorbic acid may be responsible for the labelling of sulfenic acids (RSHO) and disulfides as well. An improvement of this technique called d‐switch, allowing simultaneous detection and identification of both S‐nitrosated and non‐nitrosated cysteines by MS instead of Western blot, following derivatization with NEM, has recently been proposed (Sinha et al., 2010). Other methods are chemiluminescence‐based assays, such as the tri‐iodide and the 3C methods, which carry the same risk of artefactual cysteine‐SNO generation. In addition, these methods do not allow the identification of the S‐nitrosated residues.

Recently, direct detection of cysteine‐SNO residues by MS has been described for thioredoxin (Barglow et al., 2011), allowing simultaneous determination of the redox status of the protein. This type of approach is obviously of interest when targeting specific individual proteins but not for complex sample analysis. More promising is the current research on novel RSNO chemistry and direct labelling techniques. Among the reagents of potential interest are the triarylphosphines, which react with organic RSNOs to yield S‐substituted aza‐ylides (RS‐N = PR3) without reacting with disulphide bonds. These approaches should allow direct labelling and detection of cysteine‐SNOs without the risk of artificial modifications (Bechtold and King, 2012). Very recently, Daiber's team has developed an assay using salicylaldehyde as a probe to measure very low fluxes of ONOO− generation compatible with in vivo concentrations (Mikhed et al., 2016). This approach opens the way to a novel method allowing the determination of ONOO− generation in vivo.

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Biomarkers of tyrosine nitration

In contrast to S‐nitrosation, nitration is a stable covalent modification, which can therefore be investigated much more easily. In eukaryotes, nitration mainly affects tyrosine residues yielding 3‐nitrotyrosine (Bottari, 2015), but it can apparently also modify tryptophan residues, giving rise essentially to 6‐nitrotryptophan residues under pathophysiological conditions (Nuriel et al., 2011). Interestingly, although tyrosine nitration is not a direct, enzymically driven, post‐translational modification, the tyrosine residues affected are not random, at least under pathophysiological conditions when ONOO− fluxes remain at μM levels (Jiao et al., 2001; Csibi et al., 2010). Protein nitration in cells or tissues can easily be demonstrated by immunoblotting and immunohistochemistry provided the antibodies used are specific for nitrotyrosine residues and do not, as often, cross‐react with 3‐aminotyrosine, 3‐chlorotyrosine, orthophosphotyrosine or nitrotryptophans. This precludes the use of polyclonal antibodies and requires adequate controls, in particular reduction of the samples to be analysed with sodium thiosulfate which, by reducing nitrotyrosine to aminotyrosine, should suppress recognition by the antibody. Accordingly, SDS‐PAGE should be performed under non‐reducing conditions.

Most of the early studies regarding nitrative stress used free 3‐nitrotyrosine as a biomarker (Ohshima et al., 1990; Ceriello, 2002). However, the major part of free circulating nitrotyrosine originates from dietary proteins nitrated in the gastrointestinal tract (Lundberg et al., 2004; Rocha et al., 2012). Therefore, it cannot serve as a reliable indicator of systemic nitrative stress. The same holds for small nitrotyrosine containing peptides, which, like free nitrotyrosine, can be measured by HPLC. Another serious disadvantage of this method is the possibility of artificial nitration during the assay (Ryberg and Caidahl, 2007; Tsikas and Duncan, 2014). The same is obviously true for the 3‐nitrotyrosine metabolite 3‐nitro‐4‐hydroxyphenylacetic acid, which does not only arise from 3‐nitrotyrosine but is also a nitration product of p‐hydroxyphenylacetic acid, a metabolite of tyrosine (Mani et al., 2003; Hoehn et al., 2008). Therefore, the only reliable biomarkers for exploring systemic nitrative stress are circulating proteins which are nitrated in vivo but outside the gastrointestinal tract. A variety of nitroproteins have been identified in plasma (Piroddi et al., 2011) but so far the only quantitative assay which has been developed and clinically validated, is an elisa for nitrated albumin (Wayenberg et al., 2009, 2011). This elisa has been validated previously in studies on perinatal asphyxia where it was shown to correlate with the severity of neonatal encephalopathy (Wayenberg et al., 2009), a condition reported to be associated with increased protein nitration in the human brain (Groenendaal et al., 2006, 2008) and on neonatal hypoglycaemia where it was shown to correlate with the number and severity of hypoglycemic events (Wayenberg et al., 2011).

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Lipid peroxidation

Lipids are increasingly the aim of researchers as their roles in vital cellular processes are gradually revealed. Thus, lipids are not only essential components of the biomembranes but also are active players in signalling of the key metabolic processes. One of the most important reactions of lipids is the autocatalysed, chain‐reaction of peroxidation. Lipids that are the most susceptible for lipid peroxidation (LPO) are polyunsaturated fatty acids (PUFA). Linoleic and arachidonic acid are among the most important substrates in the process of LPO, as their degradation products are active in a wide variety of biological processes and signal transduction pathways.

The autocatalytic cascade reactions of LPO are presented in Figure 2. LPO is initiated by attack of ROS on a double bond of in the PUFA and a lipid radical (L•) is formed. Subsequently, the lipid radical reacts with molecular oxygen generating a lipid peroxyl radical (LOO•), which is crucial for the propagation of LPO without new radical species. However, at this stage LPO can be terminated by chain‐breaking antioxidants, such as β‐carotene or α‐tocopherol, which protect membrane lipids from peroxidation. If the LPO is not terminated, the LOO• subtracts a hydrogen atom from the neighbouring acyl chain leading to lipid hydroperoxide (LOOH) and new L• formation (Gueraud et al., 2010). LOOH further react with trace metals generating lipid alkoxyl radicals (LO•). LOO• and LO• are then cyclized and/or degraded to different reactive aldehydes including trans‐4‐hydroxy‐2‐nonenal (4‐HNE), trans‐4‐oxo‐2‐nonenal, acrolein (ACR) and malondialdehyde (MDA). Which of these aldehydes will be produced depends on the type of polyunsaturated fatty acid undergoing LPO.

Figure 2

Cascade reactions of lipid peroxidation.

At first, LPO was considered only as a destructive process for the cells, destroying biomembranes and generating a variety of reactive aldehydes that are toxic for the cell. Nowadays, it is known that these aldehydes are generated also under physiological conditions and participate in cellular signalling by modulating pathways crucial for cell survival and stress response. Therefore, aldehydic end‐products of LPO are now denoted as ‘second messengers of free radicals’. Even though these aldehydes can be detected as free molecules, they bind with high affinity to proteins forming ‘advanced lipoxidation end‐products’ (ALEs) (Vistoli et al., 2013). Most ALEs not only include amino acid moieties like cysteine, histidine, arginine but also crosslinks like glyoxal–lysine dimers or lysine–MDA–lysine (Vistoli et al., 2013). Although protein conjugates are probably the predominant forms of the LPO‐generated aldehydes in biological samples, their physiological roles are still not well understood. Pathological importance of ALEs in stress‐associated diseases is much better understood indicating the possibility of migrating from their site of origin (Esterbauer et al., 1991). Spiteller has already reviewed the involvement of LPO in a variety of chronic diseases 20 years ago (Spiteller, 1998), assuming that ALEs are present only in case of stress‐associated disorders. As a consequence, ALEs started to emerge as major biomarkers of OS, with 4‐HNE and MDA as the most investigated examples (Zarkovic, 2003).

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Summary of methods for detection of LPO: 4‐HNE‐His as a major bioactive marker of LPO

The most popular methods measure different classes of oxidation products such as carbonyls or hydroperoxides in a rather non‐specific manner, while other more recommendable methods are specific for a single LPO product. The inter‐laboratory study carried by 16 research teams in 2010 revealed MDA HPLC to be the method of choice for the measurement of LPO in UVA‐treated human plasma samples (Breusing et al., 2010). This chromatographic method originates from the popular, but not specific, photometric assay with thiobarbituric acid (the TBARS assay). The TBARS assay was introduced already 70 years ago by Kohn and Liversedge describing the reaction of MDA with thiobarbituric acid (TBA) under acidic conditions at high temperature (95–100°C), generating a pink‐coloured complex with absorbance at 532 nm (Kohn and Liversedge, 1944). Although TBARS mostly detects MDA, it is still considered a non‐specific and not credible method to monitor LPO, unless combined with HPLC using well‐defined MDA standards.

Besides detecting MDA by HPLC, the same inter‐laboratory study also analysed the levels of isoprostanes (F2‐IsoPs) by GC–MS and of 4‐HNE‐His adducts detected by non‐commercial elisa, based on genuine monoclonal antibodies. Both F2‐isoprostane and 4‐HNE‐elisa gave higher inter‐laboratory variations, which made these two methods less convenient than the MDA HPLC. However, it should be mentioned that the 4‐HNE‐elisa used in this study used the protocol developed for in vitro research on cell cultures and not for human plasma samples (Borovic et al., 2006, 2007). Nevertheless, the parallel analyses of several human plasma samples, by both MDA HPLC and 4‐HNE‐His elisa, gave very good correlations (0.82–0.93) indicating a potential use of the 4‐HNE‐elisa for human plasma samples.

Indeed, in 2013, the modified version of the 4‐HNE‐His elisa was described to be convenient for human plasma as well as for human sera samples (Weber et al., 2013). Interestingly, the modified version of the 4‐HNE‐His elisa used not only non‐commercial but also commercially available monoclonal antibodies, which were about 10‐fold less sensitive than the non‐commercial ones. However, the 4‐HNE‐His elisa based on commercial monoclonal antibodies resembled the 4‐HNE‐HIs elisa based on more specific, non‐commercial, monoclonal antibodies, in both cases revealing the 50% increase of the ALE products in the blood in apparently healthy, but obese, young to mid‐aged men (Weber et al., 2013). It also has to be stressed that further modification of the 4‐HNE‐His elisa was introduced this year for the detection of ALE in murine tissue homogenates, showing 50% increase of the 4‐HNE‐His adducts in livers of rats fed an PUFA‐enriched diet (Guéraud et al., 2015).

The relevance of 4‐HNE‐His adducts as biomarkers of OS is also supported by the fact that HNE‐His adducts dominate in Cu2 +‐oxidized human LDL, while the other major 4‐HNE‐derived Michael adducts (4‐HNE–lysine and 4‐HNE–cysteine) appeared in almost negligible amounts in the oxLDL, as analysed by the fluorescent probe 2‐aminopyridine labelling method recently developed by Japanese researchers (Wakita et al., 2011). Thus, the specificity and applicability of 4‐HNE‐His monoclonal antibodies allows detection of the corresponding adducts in human and animal cell cultures, tissue homogenates and in plasma and serum samples, which is of primary importance for the studies on LPO end‐products in cell signalling and regulation of proliferation, differentiation, degeneration, transformation and apoptosis. Accordingly, 4‐HNE‐His adducts are often referred to as the major biomarkers of LPO, implying the applicability of methods for their detection in various samples as well as their role in crucial cellular processes, in particular redox signalling.

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LPO end‐products and redox signalling

A biological role of the LPO end‐products, especially of 4‐HNE, was reported already in 1993, when physiological concentrations of the aldehyde added to serum were found to stimulate the growth of HeLa cells (Zarkovic et al., 1993). Since then, evidence has emerged not only for a biological role and the importance of 4‐HNE, but also of the other LPO derived aldehydes in the regulation of cellular homeostasis (Mrakovcic et al., 2010). In parallel to the discovery of physiological roles of reactive aldehydes, redox signalling pathways were being revealed. One of these pathways, affected by 4‐HNE, is the nuclear factor erythroid 2 [NF‐E2]‐related factor 2 (Nrf2)‐Keap1‐antioxidant responsive element (ARE) pathway. As long as the cellular redox state remains unaffected, Nrf2 and Keap1 form a complex. Any change in redox potential is sensed by Keap1 and results in the release of Nrf2 from the complex and its translocation to the nucleus (Jaramillo and Zhang, 2013). In the nucleus, Nrf2 binds to the ARE DNA sequence and activates the transcription of antioxidant genes such as haeme oxygenase‐1 and glutamate cysteine ligase catalytic subunit (Kuwano et al., 2015). Nrf2 is a part of a redox signalling pathway that maintains cellular homeostasis and contributes to adaptation to OS. Nrf2 is recognized as an important actor in the regulation of proliferation and differentiation that is obtained through the regulation of intracellular ROS levels (Murakami and Motohashi, 2015). The Nrf2 pathway has a very large interactome (Csala et al., 2015) and 4‐HNE modulates this pathway at different levels. Direct interaction of 4‐HNE and Keap1 is accomplished through three sensor cysteine residues of Keap1, causing dissociation and activation of Nrf2 (McMahon et al., 2010). Indirect activation of Nrf2 pathways by 4‐HNE occurs via ER stress, causing the unfolded protein response (UPR) (Vladykovskaya et al., 2012). The UPR activates protein kinase RNA‐like endoplasmic reticulum kinase, which then phosphorylates Nrf2, weakening the Nrf2‐Keap1 binding and finally releasing Nrf2 from the complex (Cullinan et al., 2003).

The Nrf2 pathway is only a small part of the interactions and pathways regulated and/or modulated by 4‐HNE. The complexity and variety of pathways modulated by 4‐HNE emphasize its relevance in human and animal pathophysiology, as well as in plant and even yeast cells. They are a good basis for a better understanding, not only of several pathological, but also of physiological processes, in particular those related to oxygen metabolism in general, as will be discussed later in this review. Therefore, methods for the detection and monitoring of 4‐HNE and in particular of 4‐HNE‐His adducts as major biomarkers of LPO are constantly being developed and eval‎uated with regard to overall health parameters.

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Qualitative analysis of 4‐HNE‐His adducts

While the previously mentioned methods are mostly quantitative and do not provide information about the distribution of the ALEs within the subcellular compartments or among the different cells in the organ/tissue, qualitative analyses are based on specific monoclonal antibodies raised against 4‐HNE and related aldehydes (mostly MDA and ACR) conjugated to proteins. Besides visualization of the distribution of ALEs obtained by immunohistochemistry, a particular advantage of the 4‐HNE‐His monoclonal antibodies resides in the fact that the very same epitopes could be detected both by qualitative and (semi)quantitative immunohistochemical methods. Moreover, while these epitopes remain stable for about 1 year if the samples are kept at −80°C, in case of immunohistochemical analyses, the samples are usually formalin‐fixed and well preserved for years, especially in the case of paraffin‐embedded tissue specimens (Figure 3). Technical aspects, advantages and pitfalls of both qualitative and quantitative methods for the LPO biomarkers have been recently described in more detail in several review articles (Spickett et al., 2010; Gasparovic et al., 2013; Frijhoff et al., 2015).

Figure 3

Immunohistochemical appearance of 4‐HNE‐His adducts (ALE) in a human cerebral blood vessel. The presence of 4‐HNE‐modified proteins can be seen only in the muscle layer of the blood vessel (brown colour), while endothelium and even the remaining blood content are negative for ALE. Recently, the association of such 4‐HNE‐His adducts in aorta was found to be related to the pathophysiology of atherosclerosis and ageing (Zarkovic et al., 2015).

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Protein carbonyls

While carbonyl groups are introduced in lysine, cysteine and histidine residues by binding of reactive aldehydes generated by LPO (Michael addition) resulting in ALEs, sulphur‐containing amino acids, the aromatic amino acids and the amino acids containing an additional nitrogen atom in the side chain can be directly attacked by ROS (Vistoli et al., 2013). Therefore, protein carbonyls are formed through oxidative cleavage of protein backbones resulting in a change of protein structure and function. As carbonyls are generated by different mechanisms, their concentration is often quite high, reducing the relevance of their detection as biomarkers of OS (Dean et al., 1997). Protein carbonyls having either aldehyde or ketone moieties are commonly detected by reaction with 2,4‐dinitrophenylhydrazine (DNP) producing carbonyl‐2,4‐dinitrophenylhydrazone adducts detectable by spectrophotometry or by anti‐DNP antibodies (Buss et al., 1997). Hence, both detection options are indirect methods for the investigation of oxidative protein modifications, which is a disadvantage in comparison to the direct qualitative or quantitative methods for the immunochemical detection of ALEs (as in case of 4‐HNE‐His), which per se also represent protein carbonylation.

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Recognition of the dualistic role of ROS and RNS sets new challenges for the eval‎uation of OS: Are the conventional biomarkers sufficient?

Increased levels of LPO products (hydroperoxides, 4‐HNE, MDA, oxidatively modified proteins (OMP), protein carbonyls, S‐nitrosothiols or oxidized nucleosides, such as 7,8‐dihydro‐8‐oxo‐2′‐deoxyguanosine, have been commonly recognized as OS biomarkers (Casas et al., 2015; Frijhoff et al., 2015; Karimi Galougahi et al., 2015). Over time, therapeutic attempts to control ROS flow and to prevent accumulation of their electron‐excited metabolites by administration of direct antioxidants (vitamins C and E, β carotene, glutathione) did not show major, if any, benefit in clinical trials. Moreover, only insignificant changes in the quantities of the OS biomarkers in blood of patients with various OS associated diseases have been reported (Biesalski et al., 2010; Bast and Haenen, 2013; Milkovic et al., 2015; Schmidt et al., 2015; Violi and Pignatelli, 2015). Our previous studies demonstrated that the onset of OS reflects the general health condition of patients and severity of their illness. The concentration of MDA, a conventional OS biomarker, was 114.7 ± 3.9 μM in type 2 diabetic patients, compared with 71.9 ± 2.2 μM in healthy volunteers and 60.9 ± 1.4 μM in elite athletes. At the same time, the levels of OMP, measured as the adducts of DNP at 370 nm, were increased both in diabetics and sportsmen (7.1 ± 0.3 and 9.1 ± 0.2 CU·mL−1 respectively), compared with 5.0 ± 0.2 CU·mL−1 in control subjects (Yelisyeyeva et al., 2012; Semen et al., 2013). These findings point out that OMP are formed by different metabolic backgrounds and different OS severities in healthy people and in diabetic patients. These findings also illustrate the importance of protein carbonyls and ALEs (both being OMPs) not only as a biomarkers of OS but also as parameters reflecting the pool of proteins that may function in oxidatively modified forms during activation of redox processes (Vollaard et al., 2005; Widmer et al., 2010). The variety of changes due to excessive ROS production make the development of an efficient algorithm aimed at elimination of oxidative damage a challenging task. On the other hand, these defects stimulate research on the methods of complex eval‎uation of OS and its correction and promote studies on the mechanisms of stress resistance (Linnane and Eastwood, 2006; Dennery, 2010; Buettner, 2015; Holzerová and Prokisch, 2015). Moreover, the evidence regarding the beneficial effects of pro‐oxidants that activate signalling pathways through expression‎ of major transcriptional factors such as HIF‐1 (Dehne and Brüne, 2014), NFkB, Nrf‐2 (Hayes and Dinkova‐Kostova, 2014; Satoh et al., 2014) and their efficient interactions have been described (Buelna‐Chontal and Zazueta, 2013; Hayes and Dinkova‐Kostova, 2014). Much attention is currently being paid to the inducers of the Nrf‐2/ARE pathways, because of their electrophilic properties and ability to act as Michael acceptors (Hybertson et al., 2011; Levonen et al., 2014). Such substances improve donor–acceptor interactions and facilitate induction of antioxidant defence.

Nowadays, it is widely accepted that radical‐triggered oxidation is one of the major regulatory mechanisms involved in a range of biological processes including redox signalling, proliferation, differentiation, apoptosis, inflammation, obesity and immune responses (Sarsour et al., 2009; Negre‐Salvayre et al., 2010; Forman et al., 2014; Daiber et al., 2016; Jankovic et al., 2016). Formation of ROS is a necessary outcome of aerobic life and its complex antioxidative defence system. On the other hand, to achieve optimal ROS flow, mild pro‐oxidant activity with the leftward shift in the pro‐/anti‐oxidant balance is required. It promotes propagation of ROS reactions, prevents their decline and helps tuning the antioxidative system in accordance with the current metabolic needs. Under such metabolic circumstances, favourable responses are activated in a process named hormesis. Hormetic reactions (from the Greek hórmēsis ‘rapid motion, eagerness’) are considered non‐specific and are the most beneficial adaptive responses aimed at increasing resistance to OS (Voeikov, 2005; Linnane and Eastwood, 2006; Ristow and Zarse, 2010; Vaiserman, 2010; Calabrese et al., 2013; Zakharchenko et al., 2013; Yelisyeyeva et al., 2014).

Constant monitoring of the balance between ROS production and elimination, the equilibrium between pro‐ and antioxidants and eval‎uation of how the oxidized metabolites are eliminated by aerobic metabolism, including their utilization by mitochondria are of greatest importance. Conventional OS biomarkers are not suitable to assess mitochondrial metabolism, which plays a key role in the regulation of the redox processes (Jezek and Hlavatá, 2005; Kowaltowski et al., 2009; Schulz et al., 2014; Jankovic et al., 2015). Increased electron flow through the respiratory chain during pro‐oxidant activation triggers a variety of mechanisms aimed at preventing hyperactivation. One of the most important mechanisms involves energy deficit (increase in the ADP/ATP ratio and decrease in the NAD+/NADH ratio), which consequently activates sirtuins (Cantó and Auwerx, 2009; Verdin et al., 2010), uncoupling proteins (Wolkow and Iser, 2006), transaminase reactions in the Krebs cycle, glyoxalate pathways (Kondrashov et al., 2006; Zakharchenko et al., 2013) and peroxisomal oxidation (Jezek and Hlavatá, 2005; Abdelmegeed et al., 2009). The level of energy deficit determines the ultimate result of the activation of aerobic metabolism. The latter can be moderate or excessive, which leads to pronounced OS. It has to be noted that moderate activation can easily progress to excessive levels as the distinction between them is very delicate, poorly controlled and thus requires constant monitoring. Therefore, there is a need for the integration of nitro‐OS biomarkers and functional activity of the organism, in particular of the vital organs, as parameters that would not only reflect the state of aerobic metabolism but also the pattern of changes during nitro‐OS and recovery from nitro‐OS‐induced damage.

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Can heart rate variability reflect severity of oxidative stress?

Non‐specific resistance to OS is reflected by variations of heart rhythm, with high resistance to OS being accompanied by highly variable heart rhythm and low resistance by low heart rate variability (HRV) and even formation of a rigid heart rhythm (Aubert et al., 2003; Christensen, 2011; Yelisyeyeva et al., 2012; Jarczok et al., 2015). The degree of variability between the heart beats can be assessed with a non‐invasive tool, HRV, that involves recording of the ECG with subsequent analysis of RR intervals (time and frequency domain indices) (Malik et al., 1996). The ultimate response of the cardiovascular system and thus of the whole organism, is reflected by three power bands in the HRV spectrogram. In general, they describe the condition of central and autonomic regulation, relationship between sympathetic and parasympathetic nervous system, baroreflex regulation and metabolic status. The cardiorespiratory system is sensitive even to very small shifts in pO2, pCO2 and also pH, which reflect the efficacy of aerobic metabolism and thus the degree of oxidative damage (Semen et al., 2010; Yelisyeyeva et al., 2012). It is widely accepted that diseases associated with OS such as diabetes, cardiovascular, neurodegenerative and inflammatory disorders, are characterized by reduced HRV (Lahiri et al., 2008; LaRovere and Christensen, 2015; Semen et al., 2016). Usually, reduced HRV (low values of total power (TP), low percentage of low frequency (LF) and high frequency (HF) bands in the spectral structure) is accompanied by increased levels of the well‐recognized biochemical markers of OS and disorders in the pro‐/antioxidant balance. Such inverse relationships were demonstrated for lipidomic indices (levels of plasma triglycerides, cholesterol, low‐density lipoprotein and high‐density lipoprotein) and for MDA (Apaijai et al., 2013; Supakul et al., 2014) and HNE (Semen et al., 2016). However, such correlations between HRV indices and certain OS biomarkers does not occur in a uniform pattern. For example, we found discrepancies between HRV indices and OMP levels in type 2 diabetes (Semen et al., 2013) suggesting that there is no clear uniform relationship between HRV parameters and levels of OS biomarkers. Therefore, more detailed features of these relationships should be further studied. One should also keep in mind that all OS biomarkers cannot be interpreted similarly as they reflect different metabolic pathways and redox signalling mechanisms. Some of these metabolites, used as biomarkers, are maintaining free radical and oxygen levels through feedback mechanisms, which affect the activity of central and autonomic regulatory components thereby modulating heart rhythm. It therefore appears that the use of HRV in research and clinical settings may provide a valuable integrated insight into the mechanisms of redox homeostasis, especially because the values of total spectral power and some spectral HRV parameters can be used to eval‎uate adaptive response and stress resistance and might have prognostic significance (Yelisyeyeva et al., 2012). The relationship between HRV parameters and functional metabolic conditions is summarized in Table 1.

Table 1

Relationship between heart rate variability (HRV) parameters (total power, TP, ms2; very low frequency, VLF, ms2; low frequency, LF, ms2; high frequency, HF, ms2) and functional metabolic conditions

ConditionHRV parametersТР (ms2)VLF (%)LF (%)HF (%)

Good (high resistance against oxidative stress)	5000–12 000	<20	20–30	60–75
Mild tension (medium resistance against oxidative stress)	2000–5000	25–40	30–45	35–45
High tension (low resistance against oxidative stress)	1000–2000	30–65	25–50	20–30
Exhaustion (very low resistance against oxidative stress)	<1000	40–70	15–25	10–25

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The depression of aerobic metabolism, reflected by low HRV, is observed during severe chronic illnesses such as neurodegenerative disease, diabetes, malignancies, cardiovascular (ischaemic) disorders and other conditions associated with OS (Valko et al., 2007; Sarsour et al., 2009; Negre‐Salvayre et al., 2010; Reuter et al., 2010). On the contrary, high intensity of redox reactions (more efficient autonomic regulation) is reflected by high HRV, with marked variance between adjacent RR intervals and a significant proportion of long RR intervals (>50 ms). High‐power aerobic metabolism prevents development of OS and hypoxia and leads to improvement of the oxygen homeostasis and autonomy of the metabolic system. This is usually accompanied by optimization of the cardiorespiratory function (Yelisyeyeva et al., 2012) and is reflected by high HRV (Table 1). High HRV suggests the involvement of endogenous oxygen in the maintenance of the О2/RO(N)S balance, especially in the mitochondria. Involvement of endogenous oxygen in the normalization of рО2 can improve functions of the oxygen‐dependent enzymes (such as SOD, catalase, glutathione peroxidase, hemoxygenase, prolyl hydroxylase, NOS, cytochrome c oxidase), which are inhibited or uncoupled under hypoxic conditions (Lahiri et al., 2006; Ward, 2008; Semenza, 2011). Moderate activation of the free radical reaction (FRR) induces oxidative damage and promotes adequate stimulation of the anti‐oxidative defences and repair of the functioning structures, especially membranes. It also involves oxidative modification of the macromolecules such as haemoglobin, tissue haemoproteins (myoglobin, cytoglobin and neuroglobin) (Burmester et al., 2007; Flögel et al., 2010) and phospholipids (Bochkov et al., 2010; Del Rio et al., 2010; Spickett and Pitt, 2015), resulting in their participation in FRR. It is suggested that haemoproteins play crucial roles in transforming the pro‐oxidant signal triggered, for example, by interval hypoxia (Prabhakar et al., 2007; Del Rio et al., 2010), or PUFA (Das, 2008; Schönfeld et al., 2011) to the mitochondria.

Taken together, such metabolic status underlies the mild pro‐oxidant activity (which is crucial for hormetic reactions) and correlates with HRV parameters (Figure 4). At the level of an organism, improvement of HRV is accompanied by better metabolic self‐organization and regulation. The outlined mechanisms of the oxygen homeostasis and redox signalling require further study, and this, in turn, will facilitate development of non‐invasive integrative diagnostic tools that can be readily used in clinical practice.

Figure 4

Metabolic background of heart rhythm modulation for hormetic reaction. HRV – heart rate variability. TP, LF, HF, SDNN, pNN50, RMSSD – HRV parameters. Frequency bands: VLF – very low frequency oscillations (0.015–0.04 Hz) reflects the neural‐hormonal activity; LF – low frequency oscillations (0.04–0.15 Hz) represents mainly sympathetic influences on the heart rate); HF – high frequency oscillations (0.15–0.4 Hz) reflects parasympathetic regulation); TP – total power (VLF+LF+HF). SDNN, pNN50, RMSSD (ms) – time parameters of HRV (which correlate with autonomic frequency bands (LF with SDNN; HF with pNN50 and RMSSD). SDNN – standard deviation of normal RR intervals RMSSD – square root of the mean squared differences of successive RR interval pNN50 percentage of differences between adjacent normal RR intervals exceeding 50 milliseconds TRP – transient receptor potential channels; ATP – adenosine triphosphate; ROS – reactive oxygen species; SDG – sulfur dioxygenase; SQR – sulfide:quinone oxidoreductase; STR – sulfur transferase (enzymes of H2S oxidation in mitochondria by the sulfide quinone oxido‐reductase (oxygen sensitive) system.

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Conclusions and perspectives

As indicated in this brief review, redox signalling is essential for the maintenance of homeostasis, at the level of the organelle, of the cell, of the tissue and organ and the organism. The mechanisms that control the generation and the degradation of reactive species, composed only of oxygen, nitrogen and hydrogen virtually regulate, in an often direct manner and through a very limited number of enzymes, most of the essential cell functions: proliferation, differentiation, death through apoptosis and metabolism. Indeed, many enzymes including kinases and phosphatases, synthases of all types, along with ion exchangers, transporters and channels, docking and structural proteins, are either affected by oxidation and reduction of cysteine residues or by post‐translational modifications due to ROS and RNS. The physiological role of these mechanisms, which have, erroneously, long been considered by many as being essentially pathological and deleterious as indicated by the associated term ‘stress’, is therefore absolutely essential. This has been further demonstrated by a series of interventional studies using various antioxidants for the primary or secondary prevention of various diseases including cardiovascular diseases, cancer, retinitis and neurodegenerative diseases as well as in ageing, which, at best, have been shown to have little or no beneficial effects, with several antioxidants prescribed at low doses and deleterious effects at higher doses (Bjelakovic, Nikolova & Gluud, 2013; Bjelakovic, Nikolova & Gluud, 2014; Ochi & Takeda, 2015; Paolini et al., 2003; Vainio, 2000; Vrolijk et al., 2015).

It is therefore of primary interest and importance to gain further insight into the molecular mechanisms of action not only of ROS and RNS but also of the many ‘antioxidants’ whose prescription and customary consumption in the Western world has been dramatically increasing over the past two decades. Biomarkers should be used in these studies to monitor the real redox potential of this large variety of compounds in vivo in order to better eval‎uate their potential benefit, but also if their detrimental side‐effects are directly linked to their redox potential or to distinct mechanisms.

Whereas a panel of more than 70 biomarkers of OS, in particular with respect to lipid oxidation and peroxidation has been developed, there is still a lack of validated biomarkers to study the outcomes of nitro‐OS or better, its status, which is often reversible and precedes oxidation in many pathological conditions.

Such new validated biomarkers should also allow the investigation of the real and true role and involvement of nitro‐OS and OS during the evolution of diseases, as well as the eval‎uation of the potential benefit of pharmacological interventions aimed at fighting it. With regard to this latter point, there is a clear need for ‘integrative’ parameters to allow the eval‎uation of the role and significance of the specific molecular biomarkers. As shown in the last section, HRV is a promising biomarker in this regard, especially as it is not invasive. The outcome of this area of research is clearly of primary interest at a time when nutritional supplements have become trendy or even common‐sense to improve health and ageing despite a cruel and desperate lack of scientifically proven benefit (Bjelakovic et al., 2012; Goszcz et al., 2015).

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Conflict of interest

The authors declare no conflicts of interest.

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Acknowledgements

The present work was supported by the European Cooperation in Science and Research (COST Action BM1203/EU‐ROS).

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Notes

Cipak Gasparovic, A. , Zarkovic, N. , Zarkovic, K. , Semen, K. , Kaminskyy, D. , Yelisyeyeva, O. , and Bottari, S. P. (2017) Biomarkers of oxidative and nitro‐oxidative stress: conventional and novel approaches. British Journal of Pharmacology, 174: 1771–1783. doi: 10.1111/bph.13673. [PMC free article] [PubMed] [Google Scholar]

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