Risk Variants Research Articles

Genomics-driven integrative analysis highlights immune-related plasma proteins for psychiatric disorders.

Genome-wide association studies (GWAS) have identified numerous variants associated with psychiatric disorders. However, it remains largely unknown on how GWAS risk variants contribute to psychiatric disorders. Through integrating two largest, publicly available, independent protein quantitative trait loci datasets of plasma protein and nine large-scale GWAS summary statistics of psychiatric disorders, we first performed proteome-wide association study (PWAS) to identify psychiatric disorders-associated plasma proteins, followed by enrichment analysis to reveal the underlying biological processes and pathways. Then, we conducted Mendelian randomization (MR) and Bayesian colocalization (COLOC) analyses, with both discovery and parallel replication datasets, to further identify protein-disorder pairs with putatively causal relationships. We finally prioritized the potential drug targets using Drug Gene Interaction Database. PWAS totally identified 112 proteins, which were significantly enriched in biological processes relevant to immune regulation and response to stimulus including regulation of immune system process (adjusted P = 1.69 × 10-7) and response to external stimulus (adjusted P = 4.13 × 10-7), and viral infection related pathways, including COVID-19 (adjusted P = 2.94 × 10-2). MR and COLOC analysis further identified 26 potentially causal protein-disorder pairs in both discovery and replication analysis. Notably, eight protein-coding genes were immune-related, such as IRF3, CSK, and ACE, five among 16 druggable genes were reported to interact with drugs, including ACE, CSK, PSMB4, XPNPEP1, and MICB. Our findings highlighted the immunological hypothesis and identified potentially causal plasma proteins for psychiatric disorders, providing biological insights into the pathogenesis and benefit the development of preventive or therapeutic drugs for psychiatric disorders.

Exploring the role of genetic variability and exposure to bisphenols and parabens on excess body weight in Spanish children

Gene-environment interaction studies are emerging as a promising tool to shed light on the reasons for the rapid increase in excess body weight (overweight and obesity). We aimed to investigate the influence of several polymorphisms on excess weight in Spanish children according to a short- and long-term exposure to bisphenols and parabens, combining individual approach with the joint effect of them. This case-control study included 144 controls and 98 cases children aged 3-12 years. Thirty SNPs in genes involved in obesity-related pathways, xenobiotic metabolism and hormone systems were genotyped using the GSA microchip technology and qPCRs with Taqman® probes. Levels of bisphenols and parabens in urine and hair were used to assess short- and long-term exposure, respectively, via UHPLC-MS/MS system. LEPR rs9436303 was identified as a relevant risk variant for excess weight (ORDom:AAvsAG+GG=2.65, p<0.001), and this effect persisted across exposure-stratified models. For long-term exposure, GPX1 rs1050450 was associated with increased excess weight at low single paraben exposure (ORGvsA=2.00, p=0.028, p-interaction=0.016), whereas LEPR rs1137101 exhibited a protective function at high co-exposure (ORDom:AAvsAG+GG=0.17, p=0.007, p-interaction=0.043). ESR2 rs3020450 (ORDom:GGvsAG+AA=5.17, p=0.020, p-interaction=0.028) and CYP2C19 rs4244285 (ORDom:GGvsAG+AA=3.54, p=0.039, p-interaction=0.285) were identified as predisposing variants at low and high co-exposure, respectively. In short-term exposure, higher odds were observed for INSIG2 rs7566605 at high bisphenol exposure (ORCvsG=2.97, p=0.035, p-interaction=0.017) and for GSTP1 rs1695 at low levels (ORDom:AAvsAG+GG=5.38, p=0.016, p-interaction=0.016). At low and medium co-exposure, SH2B1 rs7498665 (ORAvsG=0.17, p=0.015, p-interaction=0.085) and MC4R rs17782313 (ORAvsG=0.10, p=0.023, p-interaction=0.045) displayed a protective effect, whereas ESR2 rs3020450 maintained its contributing role (ORGvsA=3.12, p=0.030, p-interaction=0.010). Our findings demonstrate for the first time that understanding the genetic variation in excess weight and how the level of exposure to bisphenols and parabens might interact with it, is crucial for a more in-depth comprehension of the complex polygenic and multifactorial aetiology of overweight and obesity.

Exploring the Relationship Between NOD2 Risk Variants and First Decompensation Events in Cirrhotic Patients With Varices.

NOD2 mutations are associated with impaired gut mucosal barrier function. According to the systemic inflammation hypothesis, bacterial translocation is central in the development of decompensation. The aim was to evaluate whether the presence of NOD2 variants is associated with the development of first decompensation. Secondary analysis of prospectively collected consecutive patients with compensated cirrhosis, who were screened between 2014 and 2018. Patients with and without NOD2 variants were compared and stratified analysis according to the presence of varices was performed. 360 patients [239 (66%) men, median age 61 (53-69) years, 70 (19%) with NOD2 variants, 90 (25%) with varices] were followed for a median of 9 (4-16) months. Similar baseline characteristics were observed across NOD2 status groups, except for beta-blocker use (45% vs. 32% amongst variant carriers vs. non-carriers, p = 0.05). During follow-up, 34 patients (12%) developed their first decompensation, with no differences according to NOD2 status [HR 1.75 (95% CI 0.84-3.67)]. On multivariate analysis, only MELD remained an independent predictor of decompensation. Amongst patients with varices (n = 90), 18 (24.4%) carried a NOD2 variants, with a higher incidence of first decompensation [HR 3.00 (95% CI 1.08-8.32)], primarily due to ascites [HR 3.32 (95% CI 1.07-10.32)]. In this subgroup, MELD [HR 1.18 (95% CI 1.06-1.32)] and NOD2 variants [HR 2.91 (95% CI 0.95-8.89)] were determined to be independent predictors of decompensation. The presence of NOD2 risk variants leads to a greater incidence of first decompensation only in compensated patients with varices.

Gene-based burden tests of rare germline variants identify six cancer susceptibility genes.

Discovery of cancer risk variants in the sequence of the germline genome can shed light on carcinogenesis. Here we describe gene burden association analyses, aggregating rare missense and loss of function variants, at 22 cancer sites, including 130,991 cancer cases and 733,486 controls from Iceland, Norway and the United Kingdom. We identified four genes associated with increased cancer risk; the pro-apoptotic BIK for prostate cancer, the autophagy involved ATG12 for colorectal cancer, TG for thyroid cancer and CMTR2 for both lung cancer and cutaneous melanoma. Further, we found genes with rare variants that associate with decreased risk of cancer; AURKB for any cancer, irrespective of site, and PPP1R15A for breast cancer, suggesting that inhibition of PPP1R15A may be a preventive strategy for breast cancer. Our findings pinpoint several new cancer risk genes and emphasize autophagy, apoptosis and cell stress response as a focus point for developing new therapeutics.

A Genome-Wide Association Study (GWAS) of Takotsubo syndrome

Abstract Background Takotsubo syndrome (TS) is an acute cardiac condition of unknown etiology characterized by transient regional systolic dysfunction of the left and/or right ventricle. Several studies have suggested the importance of genetics; however, studies are limited and have presented conflicting results. Purpose To identify potential genetic risk variants associated with TS. Methods A case-control GWAS in three steps; I) A discovery study with Swedish takotsubo cases (n=260) and age- and sex-matched controls without heart disease from the UK Biobank (n=3034), II) A replication study of Swedish takotsubo cases (n=250) and sex- and age-matched Swedish controls without myocardial infarction from the Swedish coronary angiography and angioplasty register (n=229), III) A Meta-analysis of study I-II with extended controls from the UK-biobank (n=5161). Genotyping was performed using the Axiom® UK Biobank Genotyping Array including 820 000 single nucleotide polymorphisms (SNPs). After applying filters and QC control around 480 000 SNPs remained with a Bonferroni corrected p-value 1*10^-7, minor allele frequency (MAF 1.5-2%), Hardy-Weinberg (HWE) 10^-6. QC, filtering and analysis were performed in PLINK 1.9 and R v 4.0. Results In the discovery (I) 1490 SNP:s fulfilled a significance level of &amp;lt;10^-4, of which 36 SNP:s replicated (II) with a significance level of &amp;lt;10^-2, 11 reached a significance level of 10^-7 in the meta-analysis (III). One of the 36 SNP:s, rs1614887, replicated (II) with a significance level of 10^-3. This SNP is an intron variant in the butyrophilin subfamily 2 member A2 gene, a glycoprotein receptor involved in lipid, fatty-acid and sterol metabolism highly expressed in the heart. Of the 11 SNP:s with a significance level of 10^-7 in the meta-analysis (III) several risk variants were associated with psoriasis. Conclusions This is the largest GWAS of takotsubo syndrome performed so far, identifying one candidate gene and several potential risk variants. Further research of genetic risk variants in TS is warranted.

A proteome-wide association study identifies putative causal proteins for breast cancer risk.

Genome-wide association studies (GWAS) have identified more than 200 breast cancer risk-associated genetic loci, yet the causal genes and biological mechanisms for most loci remain elusive. Proteins, as final gene products, are pivotal in cellular function. In this study, we conducted a proteome-wide association study (PWAS) to identify proteins in breast tissue related to breast cancer risk. We profiled the proteome in fresh frozen breast tissue samples from 120 cancer-free European-ancestry women from the Susan G. Komen Tissue Bank (KTB). Protein expression levels were log2-transformed then normalized via quantile and inverse-rank transformations. GWAS data were also generated for these 120 samples. These data were used to build statistical models to predict protein expression levels via cis-genetic variants using the elastic net method. The prediction models were then applied to the GWAS summary statistics data of 133,384 breast cancer cases and 113,789 controls to assess the associations of genetically predicted protein expression levels with breast cancer risk overall and its subtypes using the S-PrediXcan method. A total of 6388 proteins were detected in the normal breast tissue samples from 120 women with a high detection false discovery rate (FDR) p value < 0.01. Among the 5820 proteins detected in more than 80% of participants, prediction models were successfully built for 2060 proteins with R > 0.1 and P < 0.05. Among these 2060 proteins, five proteins were significantly associated with overall breast cancer risk at an FDR p value < 0.1. Among these five proteins, the corresponding genes for proteins COPG1, DCTN3, and DDX6 were located at least 1 Megabase away from the GWAS-identified breast cancer risk variants. COPG1 was associated with an increased risk of breast cancer with a p value of 8.54 × 10-4. Both DCTN3 and DDX6 were associated with a decreased risk of breast cancer with p values of 1.01 × 10-3 and 3.25 × 10-4, respectively. The corresponding genes for the remaining two proteins, LSP1 and DNAJA3, were located in previously GWAS-identified breast cancer risk loci. After adjusting for GWAS-identified risk variants, the association for DNAJA3 was still significant (p value of 9.15 × 10-5 and adjusted p value of 1.94 × 10-4). However, the significance for LSP1 became weaker with a p value of 0.62. Stratification analyses by breast cancer subtypes identified three proteins, SMARCC1, LSP1, and NCKAP1L, associated with luminal A, luminal B, and ER-positive breast cancer. NCKAP1L was located at least 1Mb away from the GWAS-identified breast cancer risk variants. After adjusting for GWAS-identified breast cancer risk variants, the association for protein LSP1 was still significant (adjusted p value of 6.43 × 10-3 for luminal B subtype). We conducted the first breast-tissue-based PWAS and identified seven proteins associated with breast cancer, including five proteins not previously implicated. These findings help improve our understanding of the underlying genetic mechanism of breast cancer development.

Prognostic role of gene variants in sudden cardiac death risk associated to paediatric hypertrophic cardiomyopathy

Abstract Introduction Genetic testing plays an important role in diagnosis of hypertrophic cardiomyopathy (HCM), being sarcomeric genes commonly involved, particularly MYBPC3. However, arrhythmic risk related to genotype remains unclear in adults and almost unexplored in children. Hence, current sudden cardiac death (SCD) risk calculators do not include genetic information. Purpose To analyse risk of arrhythmic events associated with causal variants in MYBPC3 respecting to other genes in a paediatric cohort with non-syndromic HCM from a cardiomyopathy referral centre. Methods This retrospective study included patients with non-syndromic HCM 0-18 years old between 2009-2022. Demographic, clinical, and genetic data were collected. Genetic variants pathogenicity followed American College of Medical Genetics criteria. A positive genetic test was considered if a likely pathogenic or pathogenic variant in HCM related genes was found. Considered outcomes were SCD or a major arrhythmic cardiac event (MACE) within 5 years follow-up: recovered SCD, appropriate ICD therapy, or sustained ventricular tachycardia. Some SCD-risk estimation models (in 5 years) as HCM Risk-SCD model for patients &amp;gt;=15 y.o and/or 55 kg, ESC Guidelines paediatric algorithm, and HCM Risk-Kids model were applied. Results 77 patients were diagnosed with non-syndromic HCM. A causal variant was found in 45/73 (62%). No significant differences in cardiac phenotype were found related to genes. 10/77 patients (13%) presented a MACE in 5 years follow-up. A positive genetic study was significantly associated with having an event (p=0.011). Most patients with a positive genetic test harboured MYBPC3 variants (21/45, 47%), however only 2 patients who suffered a MACE had a causal variant in MYBPC3. Those with causal variants in genes other than MYBPC3 presented more and earlier events (p=0.022). Risk of having a MACE during follow-up was higher when presenting causal variants in genes other than MYBPC3: Hazard Ratio 18.5 (95% CI 2.31, 148), p=0.006. Applying HCM Risk-SCD calculator, model had better predictive discrimination when variable "causal variant in gene other than MYBPC3" was added in multivariate analysis, with high-risk category &amp;gt;=6% (C-statistic =0.931 vs 0.844) and intermediate-risk category 4-6% (C-statistic =0.845 vs 0.514). Same occurred with ESC Guidelines algorithm, adding that variable to 2 risk factors category (C-statistic =0.881 vs 0.742) or 1 risk factor (C-statistic =0.844 vs 0.635). HCM Risk-Kids also improved its predictive discrimination adding the genetic value to high-risk category &amp;gt;=6% (C-statistic =0.896 vs 0.796) and intermediate-risk (C-statistic =0.821 vs 0.506). Conclusions Genotype may have prognostic value in SCD risk in HCM in children. Our results suggests that causal genetic variants in genes other than MYBPC3 can lead to higher risk of SCD. Genetic information might be considered for future models of arrhythmic risk in children with HCM.

Potential use of pharmacogenetics in cardiology: genome-wide association studies of amiodarone-induced thyroid disorders

Abstract Background Amiodarone is a commonly prescribed antiarrhythmic drug used to manage supraventricular and ventricular arrhythmias. The use of amiodarone is associated with a broad range of adverse effects, including amiodarone-induced hypothyroidism (AIH) or amiodarone-induced thyrotoxicosis (AIT) (1). Both conditions are linked with increased mortality and have no known reliable risk predictors (2). Purpose We investigated the genetic underpinnings of amiodarone-induced thyroid disorders, and the clinical validity and utility of screening for genetic variants. Methods We conducted the first genome-wide association studies (GWAS) of AIH and AIT using data from three large biobanks. We compared the AUCs for SNPs identified through the above GWAS with polygenic risk scores for both hypo- and hyperthyroidism. Finally, we tested the clinical validity and utility of screening for risk variants. Results We found two risk loci for AIH. The lead variant at the first locus, rs1443438, was intronic to FOXE1 (OR 0.39, MAF = 35%, P = 1.59 × 10-42). The other lead variant, rs2209796, was located 93 kb upstream to FOXA2 (OR 0.56, MAF = 29%, P = 2.64 × 10-15: Figure 1). For AIT, we found one risk locus. The lead variant, rs2268803, was intronic to CAPZB (OR 1.81, MAF = 42%, P = 2.43 × 10-8: Figure 1). Next, we added GWAS SNPs or polygenic risk scores to risk prediction models consisting of age, sex and 4 principal components (PCs), and compared AUC estimates between risk models. Using GWAS SNPs, we found that the AIT variant increased the AUC with 6% (95%CI 1.1 – 10.3, AUC: 0.72) and 9% (95%CI 6.2 – 11.2, AUC: 0.75) for AIH, compared to the benchmark model. Both GWAS SNP models were superior to polygenic risk scores in terms of AUC (P for difference &amp;lt;0.05). The positive and negative predictive value (PPV and NPV) for the AIT-variant was 14.6% and 95.7%, respectively. For the AIH-variants combined, we found a PPV of 17% and a NPV of 95%. Conclusions Common genetic variants are associated with both amiodarone-induced hypo- and hyperthyroidism and are at this point, superior to polygenic risk scores in predicting amiodarone-induced thyroid disorders. These findings add to the potentials of pharmacogenetics in cardiology. Figure 1. Double Manhattan plot of amiodarone induced thyroid disorders. The Y-axis is the negative log10 of the P-value for each single nucleotide polymorphism. The X-axis is the chromosome, with positions on each chromosome ranging from lower to higher (left to right). The dotted line marks the threshold for genome-wide significance. Amiodoarone-induced hypothyroidism at the top, and amiodarone-induced thyrotoxicosis at the bottom.Figure 1

Micro-capture-C in vessel wall cell types identifies mechanisms underlying coronary artery disease susceptibility loci

Abstract Genetics is estimated to account for 50% of Coronary Artery Disease (CAD) risk. Genome-Wide Association Studies (GWAS) have revealed 100s of genomic loci which are associated with CAD (1). However, moving from GWAS signals to causal genes has proved challenging, slowing progress in developing interventions for CAD and other diseases. The greatest challenge in interpreting GWAS data is that only 10% of variants are in protein-coding regions and 90% are in "non-coding" genomic regions. Many of these non-coding variants are found in regulatory elements such as enhancers. Enhancers are distal regulatory elements that bind transcription factors and regulate genes up to 1 million base pairs away. This is achieved by DNA looping bringing enhancers into physical proximity with target genes. However, it is not possible to predict which gene(s) a given enhancer will regulate based on genomic location alone. We aimed to develop a generalisable workflow to solve CAD GWAS signals accurately and sensitively, by identifying causal enhancer SNPs and linking them mechanistically to output genes in a cell-type specific manner. We combined cell-specific epigenomic mapping with machine learning to prioritise 21,959 SNPs from 861 candidate CAD loci, in endothelial cells (HUVECs) and smooth muscle cells (HCASMCs). Micro-Capture-C (MCC) was used to resolve enhancer-promoter interactions at base-pair resolution (2). MNase footprinting determined differential transcription factor binding at specific enhancer SNPs. In HCASMCs, 20 putative enhancers containing CAD SNPs were found to interact with 32 genes, and in HUVECs 25 enhancers interacted with 48 genes. These genes were enriched for pathways including TGFb signalling, RUNX3 activity, and MAPK6/MAPK4 signalling. To prove causality at specific loci, heterozygous SNPs were identified in the individual primary cell lines. The interaction frequency at these elements was statistically compared between risk and non-risk alleles. For example, at the 9p21.3 locus, an enhancer containing a non-risk T allele was found to interact more strongly with the CDKN2B gene, compared to the risk G allele. Interestingly, this imbalance between allele interaction was potentiated by stimulation with TGFb, a key mediator in atherosclerosis. Furthermore, the transcription factor footprint at the SNP location was altered by the risk allele, indicating the mechanistic cause of the CAD-associated change in CDKN2B expression. We demonstrate a combined computational and experimental approach to identify causal non-coding variants in CAD risk loci, at scale. Among the key outputs of this study is the identification of the risk variant (rs1537373), output gene (CDKN2B), and specific cell type (HCASMC) underlying the 9p21.3 locus association with CAD risk. Using this approach to translate GWAS signals into cell-type specific outputs genes, will lead to a better understanding of the pathogenesis of CAD, and new therapeutic opportunities.

A novel functional IKBKE variant activating NFAT in a patient with polyarthritis and a remittent fever

BackgroundIKBKE is a negative regulator of T cell activation and one of the key activators of type I interferon (IFN) and NFκB signaling via non-classical pathways. The upstream single nucleotide polymorphism of IKBKE (rs2297550-G) is a genome-wide association study risk variant of systemic lupus erythematosus, and is associated with decreased IKBKE expression in T cells by expression quantitative trait locus analysis.Case presentationA 48-year-old female had a remittent fever, arthritis, and oral ulcers for 20 years. She had a poor response to corticosteroids or disease-modifying antirheumatic drugs, including the tumor necrosis factor-α antagonist, etanercept, and the anti-interleukin-6 receptor antibody, tocilizumab.MethodShe participated in the Initiative on Rare and Undiagnosed Disease (IRUD), and whole-exome sequencing (WES) was performed. Functional analyses were conducted by transfecting the identified variants into reporter cells to assess the activation of NFAT and NFκB signaling. Additionally, peripheral blood RNA- sequencing (RNA-seq) data were compared with those from healthy individuals to evaluate the gene expression profiles of immune cells.ResultWES identified a novel heterozygous c.1877G&amp;gt;A, p(Cys626Tyr) variant in IKBKE. Functional analysis indicated that this variant led to increased activity of NFAT (p = 0.015) and decreased activity of NFκB and type I IFN (p = 0.00068 and 0.00044, respectively). The patient had a remarkably low proportion of Naïve CD4 T cells. RNA-seq of peripheral blood immune cell subsets revealed significant differences in gene expression, especially in T cells.ConclusionA novel functional heterozygous variant in IKBKE is described in a patient with a remittent fever and arthritis. The data suggest that IKBKE is an important negative regulator of inflammation, particularly in T cells, and this IKBKE variant might be the underlying cause of a novel autoinflammatory pathology.

Identification of osteoporosis genes using family studies.

Osteoporosis is a multifactorial bone disease characterised by reduced bone mass and increased fracture risk. Family studies have made significant contribution in unravelling the genetics of osteoporosis. Yet, most of the underlying molecular and biological mechanisms remain unknown prompting the need for further studies. This review outlines the proper phenotyping and advanced genetic techniques in the form of high-throughput DNA sequencing used to identify genetic factors underlying monogenic osteoporosis in a family-based setting. The steps related to variant filtering prioritisation and curation are also described. From an evolutionary perspective, deleterious risk variants with higher penetrance tend to be rare as a result of negative selection. High-throughput sequencing (HTS) can identify rare variants with large effect sizes which are likely to be missed by candidate gene analysis or genome-wide association studies (GWAS) wherein common variants with small to moderate effect sizes are identified. We also describe the importance of replicating implicated genes, and possibly variants, identified following HTS to confirm their causality. Replication of the gene in other families, singletons or independent cohorts confirms that the shortlisted genes and/or variants are indeed causal. Furthermore, novel genes and/or variants implicated in monogenic osteoporosis require a thorough validation by means of in vitro and in vivo assessment. Therefore, analyses of families can continue to elucidate the genetic architecture of osteoporosis, paving the way for improved diagnostic and therapeutic strategies.

A novel variant BCL11B mutation in a pediatric patient with difficult‐to‐treat eosinophilic esophagitis

AbstractEosinophilic esophagitis (EoE) is an immunoinflammatory disease of the esophagus attributable to a complex interaction between genetic and environmental factors. While several genetic risk variants have been linked with EoE, we report a novel association between B‐cell lymphoma/leukemia 11B genetic mutation in a child with dysmorphic facies, developmental delays, atopic comorbidities, and difficult‐to‐treat EoE. After a prolonged course of EoE and multiple esophagogastroduodenoscopies with biopsies, this patient achieved clinical and histologic remission on a combination of swallowed topical steroids and high‐dose proton pump inhibitor (PPI) therapy. However, her EoE relapsed when we attempted to wean her off PPI, and it was finally controlled after adding PPI back to her regimen. This report underscores the importance of genetic testing in patients with unusual clinical features and difficult‐to‐treat EoE. Relevant to real‐world clinical practice, this case also raises the question of the treatment goals in children with EoE and underlying genetic mutation(s).

Hypothesis-based investigation of known AD risk variants reveals the genetic underpinnings of neuropathological lesions observed in Alzheimer’s-type dementia

Alzheimer’s disease (AD) is the leading cause of dementia worldwide. Besides neurofibrillary tangles and amyloid beta (Aβ) plaques, a wide range of co-morbid neuropathological features can be observed in AD brains. Since AD has a very strong genetic background and displays a wide phenotypic heterogeneity, this study aims at investigating the genetic underpinnings of co-morbid and hallmark neuropathological lesions. This was realized by obtaining the genotypes for 75 AD risk variants from low-coverage whole-genome sequencing data for 325 individuals from the Leuven Brain Collection. Association testing with deeply characterized neuropathological lesions revealed a strong and likely direct effect of rs117618017, a SNP in exon 1 of APH1B, with tau-related pathology. Second, a relation between APOE and granulovacuolar degeneration, a proxy for necroptosis, was also discovered in addition to replication of the well-known association of APOE with AD hallmark neuropathological lesions. Additionally, several nominal associations with AD risk genes were detected for pTDP pathology, α-synuclein lesions and pTau-related pathology. These findings were confirmed in a meta-analysis with three independent cohorts. For example, we replicated a prior association between TPCN1 (rs6489896) and LATE-NC risk. Furthermore, we identified new putative LATE-NC-linked SNPs, including rs7068231, located upstream of ANK3. We found association between BIN1 (rs6733839) and α-synuclein pathology, and replicated a prior association between USP6NL (rs7912495) and Lewy body pathology. Additionally, we also found that UMAD1 (rs6943429) was nominally associated with Lewy body pathology. Overall, these results contribute to a broader general understanding of how AD risk variants discovered in large-scale clinical genome-wide association studies are involved in the pathological mechanisms of AD and indicate the importance of downstream elimination of phenotypic heterogeneity introduced in these studies.

Identification of genetic risk variants for Type-2 Diabetes mellitus in Pakistani Pashtun population: A case-control association study

Background and Objective: Pakistan, a South Asian developing country, is experiencing a rapid increase in number of diabetes cases. High prevalence ratio of diabetes in Pakistani population and lack of genetic research studies prompted us to design this study. This present study investigated Pakistani Pashtun population for (known and novel SNPs) and its possible correlation with Type-2 Diabetes Mellitus (T2DM). Methods: This two stage (discovery &amp; validation stage), case-control association study included one thousand individuals (Patients with T2DM=500 &amp; controls=500) from eight districts of Khyber Pakhtunkhwa Pakistan. The study duration/period was from March 2018 to January 2020. In the first stage (the discovery stage) the target population was screened for known and novel T2DM-associated genetic markers. In the validation stage, identified variants were confirmed for T2DM association using MassARRAY genotyping and association analysis. Results: Exome sequencing detected eleven known and four novel/new genetic markers in the study population. Novel variants were preferred over the known for follow-up analysis/validation. Among the identified variants strong associations were confirmed for the following variants; rs1781133/ANKRD65 (OR=2.10, 95%Cl=1.06–3.08, P=0.003) rs2274791/TTLL10 (OR=1.97, 95%Cl=1.36-2.62, P=0.025), rs71628928/RNF223 (OR=1.82, 95%Cl=0.97-1.92, P=0.041), and rs609805/SCNN1D (OR=2.21, 95%Cl=1.92-3.09, P=0.001) with T2DM; other reported variants showed no noticeable association (having P&gt;0.05) with T2DM. Conclusion: This study reports new genetic risk variants for T2DM in Pashtun population providing valuable insights into the genetic basis of T2DM in this group. doi: https://doi.org/10.12669/pjms.40.10.10292 How to cite this: Jan A, Mothana RA, Kaimori JY, Muhammad T, Khan M, Ali SS, et al. Identification of genetic risk variants for Type-2 Diabetes mellitus in Pakistani Pashtun population: A case-control association study. Pak J Med Sci. 2024;40(10):2336-2343. doi: https://doi.org/10.12669/pjms.40.10.10292 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

A regulatory variant rs9379874 in T1D risk region 6p22.2 affects BTN3A1 expression regulating T cell function.

Genome-wide association studies (GWAS) have identified that 6p22.2 region is associated with type 1 diabetes (T1D) risk in the Chinese Han population. This study aims to reveal associations between this risk region and T1D subgroups and related clinical features, and further identify causal variant(s) and target gene(s) in this region. 2608 T1D and 4814 healthy controls were recruited from East, Central, and South China. Baseline data and genotyping for rs4320356 were collected. The most likely causal variant and gene were identified by bioinformatics analysis, dual-luciferase reporter assays, expression quantitative trait loci (eQTL), and functional annotation of the non-coding region within the 6p22.2 region. The leading variant rs4320356 in the 6p22.2 region was associated with T1D risk in the Chinese and Europeans. However, this variant was not significantly associated with islet function or autoimmunity. In silico analysis suggested rs9379874 was the most potential causal variant for T1D risk among thymus, spleen, and T cells, overlapping with the enhancer-related histone mark in multiple T cell subsets. Dual luciferase reporter assay and eQTL showed that the T allele of rs9379874 increased BTN3A1 expression by binding to FOXA1. Public single-cell RNA sequencing analysis indicated that BTN3A1 was related to T-cell activation, ATP metabolism, and cytokine metabolism pathways, which might contribute to T1D development. This study indicates that a functional variant rs9379874 regulates BTN3A1 expression, expanding the genomic landscape of T1D risk and offering a potential target for developing novel therapies.

Familial Renal Glucosuria and Potential Pharmacogenetic Impact on SGLT2 Inhibitors.

Renal glucosuria is a rare inheritable trait caused by loss-of-function variants in the gene that encodes SGLT2 (i.e., SLC5A2). The genetics of renal glucosuria is poorly understood and even less is known on how loss-of-function variants in SLC5A2 may affect response to SGLT2 inhibitors, a new class of medication gaining popularity to treat diabetes by artificially inducing glucosuria. We used two biobanks that link genomic with electronic health record data to study the genetics of renal glucosuria. This included 245,394 participants enrolled in the All of Us (AoU) Research Program and 11,011 enrolled in Marshfield Clinic's Personalized Research Project (PMRP). Association studies in AoU and PMRP identified 10 variants that reached an experiment-wise Bonferroni threshold in either cohort, nine were novel. PMRP was further used as a recruitment source for a prospective SGLT2 pharmacogenetic trial. During a glucose tolerance test, the trial measured urine glucose concentrations in 15 SLC5A2 variant-positive individuals and 15 matched wild types with and without an SGLT2 inhibitor. This trial demonstrated that carriers of SLC5A2 risk variants may be more sensitive to SGLT2 inhibitors compared to wild types (P=0.075). Based on population data, 2% of an ethnically diverse population carry rare variants in SLC5A2 and are at risk for renal glucosuria. As a result, 2% of individuals being treated with SGLT2 inhibitors may respond differently to this new class of medication compared to the general population suggesting a larger investigation into SLC5A2 variants and SGLT2 inhibitors is needed.

The Alzheimer's disease risk gene CD2AP functions in dendritic spines by remodeling F-actin.

CD2AP was identified as a genetic risk factor for late-onset Alzheimer's disease (LOAD). However, it is unclear how CD2AP contributes to LOAD synaptic dysfunction underlying AD memory deficits. We have shown that loss of CD2AP function increases β-amyloid (Aβ) endocytic production, but it is unknown whether it contributes to synapse dysfunction. As CD2AP is an actin-binding protein, it may also function in F-actin-rich dendritic spines, which are the excitatory postsynaptic compartments. Here, we demonstrate that CD2AP colocalizes with F-actin in dendritic spines of primary mouse cortical neurons of both sexes. Cell-autonomous depletion of CD2AP specifically reduces spine density and volume, resulting in a functional decrease in synapse formation and neuronal network activity. Post-synaptic reexpression of CD2AP, but not blocking Aβ-production, is sufficient to rescue spine density. CD2AP overexpression increases spine density, volume, and synapse formation, while a rare LOAD CD2AP mutation induces aberrant F-actin spine-like protrusions without functional synapses. CD2AP controls postsynaptic actin turnover, with the LOAD mutation in CD2AP decreasing F-actin dynamicity. Our data support that CD2AP risk variants could contribute to LOAD synapse dysfunction by disrupting spine formation and growth by deregulating actin dynamics.Significance statement CD2AP is a candidate genetic risk factor of late-onset Alzheimer's disease (LOAD) expressed in neurons with an unknown impact on synapse dysfunction, one of the causal LOAD mechanisms. Our research has revealed CD2AP as a new synaptic protein and established a connection between a LOAD genetic variant in CD2AP and synaptic dysfunction independent of beta-amyloid accumulation. This study suggests an explanation for the CD2AP-mediated predisposition to AD. Furthermore, we have found that controlling CD2AP's impact on spinal F-actin could be a potential target for therapeutic intervention against LOAD.

Rare variants and survival of patients with idiopathic pulmonary fibrosis.

The clinical course of idiopathic pulmonary fibrosis (IPF) is highly variable and unpredictable, with multiple genetic variants influencing IPF outcomes. Notably, rare pathogenic variants in telomere-related genes are associated with poorer clinical outcomes in these patients. Here we assessed whether rare qualifying variants (QVs) in monogenic adult-onset pulmonary fibrosis (PF) genes are associated with IPF survival. Using polygenic risk scores (PRS), we also evaluated the influence of common IPF risk variants in individuals carrying these QVs. We identified QVs in telomere and non-telomere genes linked to monogenic PF forms using whole-genome sequences (WGS) from 888 Pulmonary Fibrosis Foundation Patient Registry (PFFPR) individuals. We also derived a PRS for IPF (PRS-IPF) from 19 previously published common sentinel IPF variants. Using regression models, we then examined the mutual relationships of QVs and PRS-IPF and their association with survival. Validation of results was sought in WGS from an independent IPF study (PROFILE, n=472), and results from the two cohorts were meta-analyzed. Carriers of QVs in monogenic adult-onset PF genes, representing nearly 1 out of 6 IPF patients, were associated with lower PRS-IPF (Odds Ratio [OR]: 1.79; 95% Confidence Interval [CI]: 1.15-2.81; p=0.010) and shorter survival (Hazard Ratio [HR]: 1.53; 95% CI: 1.12-2.10; p=7.3×10 -3 ). Notably, carriers of pathogenic variants at telomere genes showed the strongest association with survival (HR: 1.76; 95% CI: 1.13-2.76; p=0.013). The meta-analysis of the results showed a consistent direction of effect across both cohorts. We revealed the opposite effects of QVs and PRS-IPF on IPF survival. Thus, a distinct IPF molecular subtype might be defined by QVs in monogenic adult-onset PF genes. Assessing the carrier status for QVs and modelling PRS-IPF promises to further contribute to predicting disease progression among IPF patients.

Genetic overlap between idiopathic scoliosis and schizophrenia in the general population.

Adolescent idiopathic scoliosis (AIS) and schizophrenia (SCZ) are two distinct conditions with poorly understood aetiologies that both emerge in otherwise healthy young adolescents. One rare genetic condition associated with both phenotypic outcomes is the 22q11.2 deletion (22q11DS). This microdeletion, encompassing 47 genes, occurs in approximately 1 in 2,148 live births and confers a 20-fold higher risk for both AIS and schizophrenia compared to the general population. In the general population (non-22q11DS carriers), AIS and SCZ have also been reported to be related and genetic studies suggest the involvement of genetic variants implicated in the central nervous functioning. In this study, our objective was to further investigate genetic overlaps between these conditions in the general population. Specifically, we aimed to explore the role of genes within the 22q11.2 region, not only in terms of common variants but also their potential impact on gene networks and biopathways. We used summary statistics from three genome-wide association studies (GWAS): two focused on AIS (n = 11,210), and one on schizophrenia (n = 36,989). To explore potential overlaps between the two conditions, we conducted a comparative analysis on the significance-based ranked single nucleotide polymorphisms (SNPs) that are associated with both AIS and SCZ. Next, we employed in silico analyses to assess gene-networks enrichment for the most significant SNPs and investigate the contribution of genes within the 22q11.2 region. Post-hoc analysis was conducted to explore the biological pathways correlated with SNPs significantly associated with both AIS and SCZ. The in silico analyses revealed a significant (adjusted-p < 0.05) genetic overlap between SCZ and both AIS cohorts. The top 3% of the most significant SNPs associated with both conditions exhibited a distinct enrichment cluster which is unlikely to be a result of chance (p < 3e-04). The gene-networks analyses showed a significant overlap of 26-41% with the ones involving genes in the 22q11DS region. However, there was no overlap between SNPs in this region and the most significant SNPs identified in the GWAS. This study revealed compelling evidence that beyond the shared association with 22q11DS as a rare genetic variant, AIS and SCZ exhibit common genetic risk variants and an overlap of important genes. The gene networks enriched by the most significant SNPs for both conditions also intersect with the ones involving genes in the 22q11DS region. However, SNPs within this region were not overrepresented among the most significant SNPs from GWAS for both conditions. Notably, gene networks linked to the risk for both conditions suggest an involvement of biopathways related to cellular signaling and neuronal development.

Cannabis use disorder: from neurobiology to treatment.

Cannabis has been legalized for medical and recreational purposes in multiple countries. A large number of people are using cannabis and some will develop cannabis use disorder (CUD). There is a growing recognition that CUD requires specific interventions. This Review will cover this topic from a variety of perspectives, with a particular emphasis on neurobiological findings and innovative treatment approaches that are being pursued. We will first describe the epidemiology and burden of disease of CUD, including risk factors associated with CUD (both in terms of general risk and genetic risk variants). Neurobiological alterations identified in brain imaging studies will be presented. Several psychosocial interventions that are useful for the management of CUD, including motivational enhancement therapy, behavioral and cognitive therapy, and contingency management, will be covered. Although no pharmacological interventions are yet approved for CUD, we present the most promising pharmacological interventions being tested.