Genetic Risk Scores

Genetics of T2DM and Its Chronic Complications: Are We Any Closer to the Individual Prediction of Genetic Risk?

Type 2 diabetes mellitus (T2DM) is a complex disease that has risen in global prevalence over recent decades, resulting in concomitant and enormous socio-economic impacts. In addition to the well-documented risk factors of obesity, poor dietary habits and sedentary lifestyles, genetic background plays a key role in the aetiopathogenesis of diabetes and the development of associated micro- and macrovascular complications. Recent advances in genomic research, notably next-generation sequencing and genome- wide association studies, have greatly improved the efficiency with which genetic backgrounds to complex diseases are analysed. To date, several hundred single-nucleotide polymorphisms have been associated with T2DM or its complications. Given the polygenic background to T2DM (and numerous other complex diseases), the degree of genetic predisposition can be treated as a "continuous trait" quantified by a genetic risk score. Focusing mainly on the Central European population, this review summarizes recent state-of-the-art methods that have enabled us to better determine the genetic architecture of T2DM and the utility of genetic risk scores in disease prediction.

Genetic risk score to improve prediction and treatment in gestational diabetes mellitus

Diabetes mellitus is a chronic disease caused by the interaction of genetics and the environment that can lead to chronic damage to many organ systems. Genome-wide association studies have identified accumulating single-nucleotide polymorphisms related to type 2 diabetes mellitus and gestational diabetes mellitus. Genetic risk score (GRS) has been utilized to evaluate the incidence risk to improve prediction and optimize treatments. This article reviews the research progress in the use of the GRS in diabetes mellitus in recent years and discusses future prospects.

Magical thinking in individuals with high polygenic risk for schizophrenia but no non-affective psychoses-a general population study

A strong genetic background for psychoses is well-established. Most individuals with a high genetic risk for schizophrenia, however, do not develop the disorder. We investigated whether individuals, who have a high genetic risk for schizophrenia but no non-affective psychotic disorders, are predisposed to develop milder forms of deviant thinking in terms of magical thinking. Participants came from the population-based Young Finns Study (n = 1292). The polygenic risk score for schizophrenia (PRS) was calculated on the basis of the most recent genome-wide association study (GWAS). Psychiatric diagnoses over the lifespan were collected up to 2017 from the registry of hospital care. Magical thinking was evaluated with the Spiritual Acceptance Scale (e.g., beliefs in telepathy, miracles, mystical events, or sixth sense) of the Temperament and Character Inventory in 1997, 2001, and 2012 (participants were 20-50-year-olds). We found that, among those who did not develop non-affective psychotic disorders, high PRS predicted higher magical thinking in adulthood (p = 0.001). Further, PRS predicted different developmental courses: a low PRS predicted a steady decrease in magical thinking from age 20 to 50 years, while in individuals with high PRS the decrease in magical thinking ceased in middle age so that their level of magical thinking remained higher than expected for that age. These findings remained when controlling for sex, childhood family environment, and adulthood socioeconomic factors. In conclusion, if high PRS does not lead to a non-affective psychotic disorder, it predicts milder forms of deviant thinking such as elevated magical thinking in adulthood, especially in middle age. The finding enhances our understanding of different outcomes of high genetic psychosis risk.

Ischemic Stroke Genetics: What Is New and How to Apply It in Clinical Practice?

The etiology of ischemic stroke is multifactorial. Although receiving less emphasis, genetic causes make a significant contribution to ischemic stroke genesis, especially in early-onset stroke. Several stroke classification systems based on genetic information corresponding to various stroke phenotypes were proposed. Twin and family history studies, as well as candidate gene approach, are common methods to discover genetic causes of stroke, however, both have their own limitations. Genome-wide association studies and next generation sequencing are more efficient, promising and increasingly used for daily diagnostics. Some monogenic disorders, despite covering only about 7% of stroke etiology, may cause well-known clinical manifestations that include stroke. Polygenic disorders are more frequent, causing about 38% of all ischemic strokes, and their identification is a rapidly developing field of modern stroke genetics. Current advances in human genetics provide opportunity for personalized prevention of stroke and novel treatment possibilities. Genetic risk scores (GRS) and extended polygenic risk scores (PRS) estimate cumulative contribution of known genetic factors to a specific outcome of stroke. Combining those scores with clinical information and risk factor profiles might result in better primary stroke prevention. Some authors encourage the use of stroke gene panels for stroke risk evaluation and further stroke research. Moreover, new biomarkers for stroke genetic causes and novel targets for gene therapy are on the horizon. In this article, we summarize the latest evidence and perspectives of ischemic stroke genetics that could be of interest to the practitioner and useful for day-to-day clinical work.

Estimating prevalence of human traits among populations from polygenic risk scores

The genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

Association of single nucleotide polymorphisms with insulin secretion, insulin sensitivity, and diabetes in women with a history of gestational diabetes mellitus

Background

This study investigated whether single nucleotide polymorphisms (SNPs) reported by previous genome-wide association studies (GWAS) to be associated with impaired insulin secretion, insulin resistance, and/or type 2 diabetes are associated with disposition index, the homeostasis model assessment of insulin resistance (HOMA-IR), and/or development of diabetes following a pregnancy complicated by gestational diabetes mellitus (GDM).

Methods

Seventy-two SNPs were genotyped in 374 women with previous GDM from Southern Sweden. An oral glucose tolerance test was performed 1–2 years postpartum, although data on the diagnosis of diabetes were accessible up to 5 years postpartum. HOMA-IR and disposition index were used to measure insulin resistance and secretion, respectively.

Results

The risk A-allele in the rs11708067 polymorphism of the adenylate cyclase 5 gene (ADCY5) was associated with decreased disposition index (beta = − 0.90, SE 0.38, p = 0.019). This polymorphism was an expression quantitative trait loci (eQTL) in islets for both ADCY5 and its antisense transcript. The risk C-allele in the rs2943641 polymorphism, near the insulin receptor substrate 1 gene (IRS1), showed a trend towards association with increased HOMA-IR (beta = 0.36, SE 0.18, p = 0.050), and the T-allele of the rs4607103 polymorphism, near the ADAM metallopeptidase with thrombospondin type 1 motif 9 gene (ADAMTS9), was associated with postpartum diabetes (OR = 2.12, SE 0.22, p = 0.00055). The genetic risk score (GRS) of the top four SNPs tested for association with the disposition index using equal weights was associated with the disposition index (beta = − 0.31, SE = 0.29, p = 0.00096). In addition, the GRS of the four SNPs studied for association with HOMA-IR using equal weights showed an association with HOMA-IR (beta = 1.13, SE = 0.48, p = 9.72874e−11). All analyses were adjusted for age, body mass index, and ethnicity.

Conclusions

This study demonstrated the genetic susceptibility of women with a history of GDM to impaired insulin secretion and sensitivity and, ultimately, to diabetes development.

Performing post-genome-wide association study analysis: overview, challenges and recommendations

Genome-wide association studies (GWAS) provide  huge information on statistically significant single-nucleotide polymorphisms (SNPs) associated with various human complex traits and diseases. By performing GWAS studies, scientists have successfully identified the association of hundreds of thousands to  millions of SNPs to a single phenotype. Moreover, the association of some SNPs with rare diseases has been intensively tested. However, classic GWAS studies have not yet provided solid, knowledgeable insight into functional and biological mechanisms underlying phenotypes or mechanisms of diseases. Therefore, several post-GWAS (pGWAS) methods have been recommended. Currently, there is no simple scientific document to provide a quick guide for performing pGWAS analysis. pGWAS is a crucial step for a better understanding of the biological machinery beyond the SNPs. Here, we provide an overview to performing pGWAS analysis and demonstrate the challenges behind each method. Furthermore, we direct readers to key articles for each pGWAS method and present the overall issues in pGWAS analysis.  Finally, we include a custom pGWAS pipeline to guide new users when performing their research.

Interaction of HLA Class II rs9272219 and TMPO rs17028450 (Arg690Cys) Variants Affects Neuromyelitis Optica Spectrum Disorder Susceptibility in an Admixed Mexican Population

Neuromyelitis Optica Spectrum Disorder (NMOSD) is a demyelinating autoimmune disease of the central nervous system, more prevalent in individuals of non-European ancestry. Few studies have analyzed genetic risk factors in NMOSD, and HLA class II gene variation has been associated NMOSD risk in various populations including Mexicans. Thymopoietin (TMPO) has not been tested as a candidate gene for NMOSD or other autoimmune disease, however, experimental evidence suggests this gene may be involved in negative selection of autoreactive T cells and autoimmunity. We thus investigated whether the missense TMPO variant rs17028450 (Arg630Cys, frequent in Latin America) is associated with NMOSD, and whether this variant shows an interaction with HLA-class II rs9272219, previously associated with NMOSD risk. A total of 119 Mexican NMOSD patients, 1208 controls and 357 Native Mexican individuals were included. The HLA rs9272219 “T” risk allele frequency ranged from 21 to 68%, while the rs17028450 “T” minor allele frequency was as high as 18% in Native Mexican groups. Both rs9272219 and rs17028450 were significantly associated with NMOSD risk under additive models (OR = 2.48; p = 8 × 10^–10 and OR = 1.59; p = 0.0075, respectively), and a significant interaction between both variants was identified with logistic regression models (p = 0.048). Individuals bearing both risk alleles had an estimated 3.9-fold increased risk of NMOSD. To our knowledge, this is the first study reporting an association of TMPO gene variation with an autoimmune disorder and the interaction of specific susceptibility gene variants, that may contribute to the genetic architecture of NMOSD in admixed Latin American populations.

Epicardial Adipose Tissue: The Genetics Behind an Emerging Cardiovascular Risk Marker

Evidence points epicardial adipose tissue (EAT) as an emerging cardiovascular risk marker. Whether genetic polymorphisms linked with atherosclerosis are associated with higher EAT is still unknown. We aim to assess the role of genetic burden of atherosclerosis and its association to EAT in a cohort of asymptomatic individuals without coronary disease. A total of 996 participants were prospectively enrolled in a single Portuguese center. EAT volume was measured by Cardiac Computed Tomography and participants were distributed into 2 groups, above and below median EAT. SNPs were genotyped and linked to their respective pathophysiological axes. A multiplicative genetic risk score (mGRS) was constructed, representing the genetic burden of the studied SNPs. To evaluate the association between genetics and EAT, we compared both groups by global mGRS, mGRS by functional axes, and SNPs individually. Individuals above-median EAT were older, had a higher body mass index (BMI) and higher prevalence of hypertension, metabolic syndrome, diabetes, and dyslipidemia. They presented higher GRS, that remained an independent predictor of higher EAT volumes. The group with more EAT consistently presented higher polymorphic burden across numerous pathways. After adjustment, age, BMI, and mGRS of each functional axis emerged as independently related to higher EAT volumes. Amongst the 33 SNPs, MTHFR677 polymorphism emerged as the only significant and independent predictor of higher EAT volumes. Patients with higher polymorphism burden for atherosclerosis present higher EAT volumes. We present the first study in a Portuguese population, evaluating the genetic profile of EAT through GWAS and GRS, casting further insight into this complicated matter.

Clinical and Genetic Risk Factors Associated With the Presence of Lupus Nephritis

Objective

To elucidate whether clinical features and the weighted genetic risk score (wGRS) were associated with the presence of lupus nephritis (LN).

Methods

We retrospectively divided patients with systemic lupus erythematosus (SLE, n=1,078) into biopsy-proven LN (n=507) and non-LN groups (non-LN, n=571) Baseline clinical features, serologic markers, and the wGRS were collected The wGRS was calculated from 112 non-human leukocyte antigen (non-HLA) loci and HLA-DRβ1 amino acid haplotypes for SLE Associations among clinical features, wGRS, and the presence of LN were identified.

Results

In the multivariate analysis, patients with LN were younger at diagnosis (odds ratio [OR]=0.97, p<0.001), had more pleuritis (OR=2.44, p<0.001) and pericarditis (OR=1.62, p=0.029), had a higher detection rate of anti-double stranded deoxyribonucleic acid (anti-dsDNA antibodies, OR=2.22, p<0.001), anti-Smith antibodies (anti-Sm antibodies, OR=1.70, p=0.002), low level of complement (OR=1.37, p=0.043) and absence of antiphospholipid antibodies (aPL antibodies, OR=1.60, p=0.002), and had higher wGRS (OR=1.16, p=0.012) Mediation analysis suggested that anti-Sm antibodies and low complement could be mediators in the relationship between high wGRS and the presence of LN.

Conclusion

Onset age, pleuritis, pericarditis, several serologic markers, and wGRS were associated with the presence of LN Anti-Sm antibodies and low complement appeared to mediate the indirect relationship between wGRS and the presence of LN.

Polygenic Risk Scores

As genome-wide association studies have continued to identify loci associated with complex traits, the implications of and necessity for proper use of these findings, including prediction of disease risk, have become apparent. Many complex diseases have numerous associated loci with detectable effects implicating risk for or protection from disease. A common contemporary approach to using this information for disease prediction is through the application of genetic risk scores. These scores estimate an individual's liability for a specific outcome by aggregating the effects of associated loci into a single measure as described in the previous version of this article. Although genetic risk scores have traditionally included variants that meet criteria for genome-wide significance, an extension known as the polygenic risk score has been developed to include the effects of more variants across the entire genome. Here, we describe common methods and software packages for calculating and interpreting polygenic risk scores. In this revised version of the article, we detail information that is needed to perform a polygenic risk score analysis, considerations for planning the analysis and interpreting results, as well as discussion of the limitations based on the choices made. We also provide simulated sample data and a walkthrough for four different polygenic risk score software. © 2021 Wiley Periodicals LLC.

Genetics of Cardiovascular Disease: How Far Are We from Personalized CVD Risk Prediction and Management?

Despite the rapid progress in diagnosis and treatment of cardiovascular disease (CVD), this disease remains a major cause of mortality and morbidity. Recent progress over the last two decades in the field of molecular genetics, especially with new tools such as genome-wide association studies, has helped to identify new genes and their variants, which can be used for calculations of risk, prediction of treatment efficacy, or detection of subjects prone to drug side effects. Although the use of genetic risk scores further improves CVD prediction, the significance is not unambiguous, and some subjects at risk remain undetected. Further research directions should focus on the "second level" of genetic information, namely, regulatory molecules (miRNAs) and epigenetic changes, predominantly DNA methylation and gene-environment interactions.

Molecular Genetics of Glaucoma: Subtype and Ethnicity Considerations

Glaucoma, the world’s leading cause of irreversible blindness, is a complex disease, with differential presentation as well as ethnic and geographic disparities. The multifactorial nature of glaucoma complicates the study of genetics and genetic involvement in the disease process. This review synthesizes the current literature on glaucoma and genetics, as stratified by glaucoma subtype and ethnicity. Primary open-angle glaucoma (POAG) is the most common cause of glaucoma worldwide, with the only treatable risk factor (RF) being the reduction of intraocular pressure (IOP). Genes associated with elevated IOP or POAG risk include: ABCA1, AFAP1, ARHGEF12, ATXN2, CAV1, CDKN2B-AS1, FOXC1, GAS7, GMDS, SIX1/SIX6, TMCO1, and TXNRD2. However, there are variations in RF and genetic factors based on ethnic and geographic differences; it is clear that unified molecular pathways accounting for POAG pathogenesis remain uncertain, although inflammation and senescence likely play an important role. There are similar ethnic and geographic complexities in primary angle closure glaucoma (PACG), but several genes have been associated with this disorder, including MMP9, HGF, HSP70, MFRP, and eNOS. In exfoliation glaucoma (XFG), genes implicated include LOXL1, CACNA1A, POMP, TMEM136, AGPAT1, RBMS3, and SEMA6A. Despite tremendous progress, major gaps remain in resolving the genetic architecture for the various glaucoma subtypes across ancestries. Large scale carefully designed studies are required to advance understanding of genetic loci as RF in glaucoma pathophysiology and to improve diagnosis and treatment options.