Editorial: Recent advances in nutrigenomics: Making strides towards precision nutrition

Precision medicine brings hope and draws attention towards advances in nutrigenomics research which elucidates the synergistic roles nutrition and genetics play in human health. In this Research Topic of Frontiers in Genetics and Frontiers in Nutrition – Nutrigenomics, forward-thinking reviews and original research manuscripts provided by experts in the field promote cutting edge computational and statistical approaches, discover novel nutrigenetic relationships, and provide critical guidance on evaluating and implementing nutrigenetic findings in a clinical setting to improve human health. Functional food ingredients that have a scientifically backed impact on human health and disease are in high demand with consumers looking for both more products and more information on their source, activity, and safety. Identifying and characterizing impactful bioactives is a tedious process, typically done in a wet-lab, using specialized and expensive instruments. Doherty et al. outline the enormous potential for artificial intelligence-led functional food ingredient discovery, validation, and characterization to address these challenges in a high-throughput manner. The authors argue for an artificial intelligence integrated workflow that complements traditional approaches from the start, highlighting its power in two case studies: the discovery of Asian rice as a potential anti-inflammatory food based on predicted immunomodulatory peptides and the characterization of peptide function in a hydrolysate derived from Vicia faba (i.e., broad beans) previously shown to prevent muscle atrophy. These approaches pave the way for future work integrating naturally occurring genetic variation in both the food compound and the human host to understand how these genetic effects may modify efficacy and implementation in precision health. Obesity is one of the main risk factors associated with the development of non-communicable diseases (i.e., cardiovascular disease, type 2 diabetes, hypertension, cancer, etc.), worldwide. To create preventive strategies against obesity and its sequelae, there is a need to develop approaches that integrate genetics, epigenetics, environmental factors, and their complex interactions. Using data from the Framingham Heart Study (N = 1,573), Lee et al. combined a genome-wide and epigenome-wide scan for body mass index with 397 dietary and lifestyle factors and their interactions using the generalized multifactor dimensionality reduction method to identify significant predictors of obesity (213 SNPs, 530 differentially methylated sites [DMs], and 49 dietary and lifestyle factors), and then compared machine learning algorithms to identify the model with the best prediction accuracy in an independent sample (N = 394) from the same cohort. The stochastic gradient boosting model achieved an ROC = 0.72 and its top predictors included 21 SNPs and 230 DMs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1 and 26 dietary factors with processed meat, calcium intake, and diet soda at the top. While it is clear that nutrition plays a role in many chronic diseases and overall human health, there is limited consistent evidence which point to causal relationships between specific foods, dietary patterns, and human disease. Using Mendelian randomization (MR) genetic instrumental variable analysis, Taba et al. apply a novel method in refining genetic instruments for MR by selecting SNPs which do not demonstrate mediation by common factors such as body mass index, educational attainment, and many others. They apply this approach to assess the causal effects between 40 foods and dietary patterns and 123 blood metabolites, representing some of the most likely intermediates on the path from diet to human disease. Together with their more recently published work (Pirastu et al., 2022), the team of authors shed light on the potential for nutritional MR studies to uncover causal associations between food intake and human traits, bringing us one step closer to more efficient randomized controlled-trials and a deeper mechanistic understanding of the role foods play in the human body. While nutrigenetics offers the promise of bringing precision nutrition to reality, many findings do not surpass or even undergo rigorous evaluation of scientific validity, an imperative first step for implementation into clinical practice. In order to make assertions about scientific validity of nutrigenetic findings, current frameworks and scoring approaches need to be evaluated, updated, and recommended for more standard use. Therefore, Keathley et al. conducted a systemic review of evidence evaluation frameworks in the fields of nutrition and/or genetics as they could be applied to nutrigenetics. They used a detailed categorization matrix with factors ranging from study design to biological plausibility, defined and refined by both an expert working group and an external expert panel, to evaluate 41 existing frameworks and in the end, recommended Keathley et al. (2022); Boffetta et al. (2012) framework with minor modifications for future use. Once gene-diet interactions are scientifically validated, then clinical utility, social implications, ease and/or barriers to implementation, and many other factors need be assessed as clinical practice guidelines are developed. Though clinical practice guidelines in nutrigenetics do not yet exist, they could be an effective tool for clinical care providers and policy makers to translate scientifically valid findings to healthcare. In a previously published article by Keathley et al. (2022), the authors use a modified GRADE framework (scoring high in the aforementioned categorization matrix) to assess the scientific validity of two key nutrigenetic findings: 1) male APOE-E carriers and 2) low 31-SNP nutrigenetic risk score in overweight and obese adults – both in the context of triglyceride changes in response to omega 3 fatty acids eicosapentaenoic acid (EPA) and/or docosahexaenoic acid (DHA). In the current perspective article Keathley et al., the authors apply the AGREE II approach to consider desirable and undesirable impacts, values and preferences, and resource use to develop clinical practice guidelines. The first recommendation of which is that triglyceride responsiveness to EPA/DHA omega-3 fatty acids in males can be based on APOE SNPs (rs429358, rs7412), however, given the link between this locus and Alzheimer’s Disease, care-providers need to comply with local regulations and patient consent while also considering ethical and legal implications of this test. The second recommendation confirms the use of previously published 31-SNP nutrigenetic risk score to evaluate TG responsive to EPA/DHA supplementation in both male and female overweight or obese adults. Their final recommendation is to not use these nutrigenetic findings for plasma lipids, lipoproteins and apolipoproteins given the current available evidence. Within this Special Section in Nutrigenomics, we offer but a glimpse on many aspects of diet and nutrition, nutrition’s role in health and disease, and the practical implementation of bringing precision nutrition to the public

Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease

Aims/hypothesis Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR9.3x10(-9)). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A and MFF; p Conclusions/interpretation Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html).Peer reviewe

Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias

Online and social networking interventions for the treatment of depression in young people: a systematic review

BACKGROUND: Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, depression displays a relapse-remitting and increasingly severe course. Given this, the development of cost-effective, acceptable, and population-focused interventions for depression is critical. A number of online interventions (both prevention and acute phase) have been tested in young people with promising results. As these interventions differ in content, clinician input, and modality, it is important to identify key features (or unhelpful functions) associated with treatment outcomes. OBJECTIVE: A systematic review of the research literature was undertaken. The review was designed to focus on two aspects of online intervention: (1) standard approaches evaluating online intervention content in randomized controlled designs (Section 1), and (2) second-generation online interventions and services using social networking (eg, social networking sites and online support groups) in any type of research design (Section 2). METHODS: Two specific literature searches were undertaken. There was no date range specified. The Section 1 search, which focused on randomized controlled trials, included only young people (12-25 years) and yielded 101 study abstracts, of which 15 met the review inclusion criteria. The Section 2 search, which included all study design types and was not restricted in terms of age, yielded 358 abstracts, of which 22 studies met the inclusion criteria. Information about the studies and their findings were extracted and tabulated for review. RESULTS: The 15 studies identified in Section 1 described 10 trials testing eight different online interventions, all of which were based on a cognitive behavioral framework. All but one of the eight identified studies reported positive results; however, only five of the 15 studies used blinded interviewer administered outcomes with most trials using self-report data. Studies varied significantly in presentation of intervention content, treatment dose, and dropout. Only two studies included moderator or clinician input. Results for Section 2 were less consistent. None of the Section 2 studies reported controlled or randomized designs. With the exception of four studies, all included participants were younger than 25 years of age. Eight of the 16 social networking studies reported positive results for depression-related outcomes. The remaining studies were either mixed or negative. Findings for online support groups tended to be more positive; however, noteworthy risks were identified. CONCLUSIONS: Online interventions with a broad cognitive behavioral focus appear to be promising in reducing depression symptomology in young people. Further research is required into the effectiveness of online interventions delivering cognitive behavioral subcomponents, such as problem-solving therapy. Evidence for the use of social networking is less compelling, although limited by a lack of well-designed studies and social networking interventions. A range of future social networking therapeutic opportunities are highlighted

Behavioural and demographic predictors of adherence to three consecutive faecal occult blood test screening opportunities: a population study

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background Social cognitive variables are often examined for their association with initial participation in colorectal cancer screening. Few studies have examined the association of these variables with adherence to multiple screening offers i.e., rescreening. This study aimed to describe patterns of participatory behaviour after three rounds of screening using faecal immunochemical tests (FIT) and to determine social cognitive, demographic and background variables predictive of variations in adherence. Methods Participants were 1,540 men and women aged 50 to 75 living in South Australia who completed a behavioural survey measuring demographic (for example, age, gender) and social cognitive variables relevant to FIT screening (for example, perceived barriers, benefits, self-efficacy). The survey was followed by three, free FIT screening offers mailed on an annual basis from 2008 to 2010. Patterns of participation after three screening rounds were described as one of five screening behaviours; 1) consistent re-participation (adherent with all screening rounds), 2) consistent refusal (adherent with no screening rounds), 3) drop out (adherent with earlier but not later rounds), 4) intermittent re-participation (adherent with alternate rounds) and 5) delayed entry (adherent with later but not initial round(s)). Univariate (Chi Square and Analysis of Variance) and multivariate (Generalised Estimating Equations) analyses were conducted to determine variables predictive of each category of non-adherence (those that did not participate in every screening offer, groups 2, 3, 4 and 5) relative to consistent re-participation. Results Significant social cognitive predictors of non-adherence were; less self-efficacy (drop out and consistent refusal), greater perceived barriers (drop out) and lower levels of response efficacy (consistent refusal). Demographic predictors of non-adherence included; male gender (delayed entry), younger age (intermittent, delayed and consistent refusal), less frequent GP visits (intermittent re-participation) and lack of adequate health insurance (drop out). Less satisfaction with screening at baseline predicted drop out, consistent refusal and delayed entry. Conclusions Different combinations of demographic and behavioural variables predicted different patterns of rescreening adherence. Rescreening interventions may benefit from a targeted approach that considers the different needs of the population subgroups. Satisfaction with past FOBT screening measured prior to the study screening offers was an important predictor of adherence

The impact of strabismus on quality of life in adults with and without diplopia: a systematic review

Strabismus affects approximately 4% of the adult population and can cause substantial physical disturbance and changes to appearance. This article aims to examine the impact of strabismus in adults both with and without diplopia, focusing primarily on quality of life (QoL). We highlight the value of measuring QoL, assess the ways in which it can be measured, and the impact the disease, diplopia, and surgery have on the patient. QoL differs for strabismus patients based on their diplopia status. Patients with diplopia tend to have more concerns relating to functional QoL, whereas patients without diplopia have primarily psychosocial concerns. Two diplopia-specific questionnaires have been designed to assess QoL and the perceived severity of symptoms. Further research is needed to identify the variables which influence QoL so that appropriate support can be given to all patients with strabismus to improve their QoL

Genome-wide association study of a nicotine metabolism biomarker in African American smokers:impact of chromosome 19 genetic influences

BACKGROUND AND AIMS: The activity of CYP2A6, the major nicotine-inactivating enzyme, is measurable in smokers using the nicotine metabolite ratio (NMR; 3'hydroxycotinine/cotinine). Due to its role in nicotine clearance, the NMR is associated with smoking behaviours and response to pharmacotherapies. The NMR is highly heritable (~80%), and on average lower in African Americans (AA) versus whites. We previously identified several reduce and loss-of-function CYP2A6 variants common in individuals of African descent. Our current aim was to identify novel genetic influences on the NMR in AA smokers using genome-wide approaches. DESIGN: Genome-wide association study (GWAS). SETTING: Multiple sites within Canada and the United States. PARTICIPANTS: AA smokers from two clinical trials: Pharmacogenetics of Nicotine Addiction Treatment (PNAT)-2 (NCT01314001; n = 504) and Kick-it-at-Swope (KIS)-3 (NCT00666978; n = 450). MEASUREMENTS: Genome-wide SNP genotyping, the NMR (phenotype) and population substructure and NMR covariates. FINDINGS: Meta-analysis revealed three independent chromosome 19 signals (rs12459249, rs111645190 and rs185430475) associated with the NMR. The top overall hit, rs12459249 (P = 1.47e-39; beta = 0.59 per C (versus T) allele, SE = 0.045), located ~9.5 kb 3' of CYP2A6, remained genome-wide significant after controlling for the common (~10% in AA) non-functional CYP2A6*17 allele. In contrast, rs111645190 and rs185430475 were not genome-wide significant when controlling for CYP2A6*17. In total, 96 signals associated with the NMR were identified; many were not found in prior NMR GWASs in individuals of European descent. The top hits were also associated with the NMR in a third cohort of AA (KIS2; n = 480). None of the hits were in UGT or OCT2 genes. CONCLUSIONS: Three independent chromosome 19 signals account for ~20% of the variability in the nicotine metabolite ratio in African American smokers. The hits identified may contribute to inter-ethnic variability in nicotine metabolism, smoking behaviours and tobacco-related disease risk

The effect of LRRK2 loss-of-function variants in humans

Analysis of large genomic datasets, including gnomAD, reveals that partial LRRK2 loss of function is not strongly associated with diseases, serving as an example of how human genetics can be leveraged for target validation in drug discovery. Human genetic variants predicted to cause loss-of-function of protein-coding genes (pLoF variants) provide natural in vivo models of human gene inactivation and can be valuable indicators of gene function and the potential toxicity of therapeutic inhibitors targeting these genes(1,2). Gain-of-kinase-function variants in LRRK2 are known to significantly increase the risk of Parkinson's disease(3,4), suggesting that inhibition of LRRK2 kinase activity is a promising therapeutic strategy. While preclinical studies in model organisms have raised some on-target toxicity concerns(5-8), the biological consequences of LRRK2 inhibition have not been well characterized in humans. Here, we systematically analyze pLoF variants in LRRK2 observed across 141,456 individuals sequenced in the Genome Aggregation Database (gnomAD)(9), 49,960 exome-sequenced individuals from the UK Biobank and over 4 million participants in the 23andMe genotyped dataset. After stringent variant curation, we identify 1,455 individuals with high-confidence pLoF variants in LRRK2. Experimental validation of three variants, combined with previous work(10), confirmed reduced protein levels in 82.5% of our cohort. We show that heterozygous pLoF variants in LRRK2 reduce LRRK2 protein levels but that these are not strongly associated with any specific phenotype or disease state. Our results demonstrate the value of large-scale genomic databases and phenotyping of human loss-of-function carriers for target validation in drug discovery.Peer reviewe

Discovery of expression QTLs using large-scale transcriptional profiling in human lymphocytes

Quantitative differences in gene expression are thought to contribute to phenotypic differences between individuals. We generated genome-wide transcriptional profiles of lymphocyte samples from 1,240 participants in the San Antonio Family Heart Study. The expression levels of 85% of the 19,648 detected autosomal transcripts were significantly heritable. Linkage analysis uncovered 41,000 cis-regulated transcripts at a false discovery rate of 5% and showed that the expression quantitative trait loci with the most significant linkage evidence are often located at the structural locus of a given transcript. To highlight the usefulness of this much-enlarged map of cis-regulated transcripts for the discovery of genes that influence complex traits in humans, as an example we selected high-density lipoprotein cholesterol concentration as a phenotype of clinical importance, and identified the cis-regulated vanin 1 (VNN1) gene as harboring sequence variants that influence high-density lipoprotein cholesterol concentrations. Phenotypic differences among individuals are partly the result of quantitative differences in transcript abundance. Although environmental stimuli may influence the location, timing, and/or level of transcription of specific genes, genetic differences among individuals are also known to have a significant role. Transcript levels may be thought of as quantitative endophenotypes that can be subjected to statistical genetic analyses in an effort to localize and identify the underlying genetic factors, an approach that is sometimes referred to as genetical genomics 1 . Using microarray technology, it is now possible to assess the abundance of many transcripts-and, indeed, of the entire known transcriptome-simultaneously. Studies that attempt to localize the genetic regulators of gene expression have been carried out in several species, including yeast 2-5 , plants (maize and eucalyptus) 6,7 , fly 8 , mouse 6,9,10 and rat 11 . Several recent investigations have also focused on humans. In most of these studies, microarray-based gene expression profiles were generated for transformed cell lines derived from lymphocytes from members of the Centre d'Etude du Polymorphisme Humain (CEPH) families 12 , and linkage and/or linkage disequilibrium approaches were used to map the genetic determinants that regulate the expression of individual transcript

Introduction: Toward an Engaged Feminist Heritage Praxis

We advocate a feminist approach to archaeological heritage work in order to transform heritage practice and the production of archaeological knowledge. We use an engaged feminist standpoint and situate intersubjectivity and intersectionality as critical components of this practice. An engaged feminist approach to heritage work allows the discipline to consider women’s, men’s, and gender non-conforming persons’ positions in the field, to reveal their contributions, to develop critical pedagogical approaches, and to rethink forms of representation. Throughout, we emphasize the intellectual labor of women of color, queer and gender non-conforming persons, and early white feminists in archaeology