Kevin L. Boehme

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study

Background Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). Methods and Findings We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Conclusions Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.

Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease

Identifying accurate biomarkers of cognitive decline is essential for advancing early diagnosis and prevention therapies in Alzheimers disease. The Alzheimers disease DREAM Challenge was designed as a computational crowdsourced project to benchmark the current state‐of‐the‐art in predicting cognitive outcomes in Alzheimers disease based on high dimensional, publicly available genetic and structural imaging data. This meta‐analysis failed to identify a meaningful predictor developed from either data modality, suggesting that alternate approaches should be considered for prediction of cognitive performance.

Genome-Wide Sensitivity Analysis of the Microsymbiont Sinorhizobium meliloti to Symbiotically Important, Defensin-Like Host Peptides

The model legume species Medicago truncatula expresses more than 700 nodule-specific cysteine-rich (NCR) signaling peptides that mediate the differentiation of Sinorhizobium meliloti bacteria into nitrogen-fixing bacteroids. NCR peptides are essential for a successful symbiosis in legume plants of the inverted-repeatlacking clade (IRLC) and show similarity to mammalian defensins. In addition to signaling functions, many NCR peptides exhibit antimicrobial activity in vitro and in vivo. Bacterial resistance to these antimicrobial activities is likely to be important for symbiosis. However, the mechanisms used by S. meliloti to resist antimicrobial activity of plant peptides are poorly understood. To address this, we applied a global genetic approach using transposon mutagenesis followed by high-throughput sequencing (Tn-seq) to identify S. meliloti genes and pathways that increase or decrease bacterial competitiveness during exposure to the well-studied cationic NCR247 peptide and also to the unrelated model antimicrobial peptide polymyxin B. We identified 78 genes and several diverse pathways whose interruption alters S. meliloti resistance to NCR247. These genes encode the following: (i) cell envelope polysaccharide biosynthesis and modification proteins, (ii) inner and outer membrane proteins, (iii) peptidoglycan (PG) effector proteins, and (iv) non-membrane-associated factors such as transcriptional regulators and ribosomeassociated factors. We describe a previously uncharacterized yet highly conserved peptidase, which protects S. meliloti from NCR247 and increases competitiveness during symbiosis. Additionally, we highlight a considerable number of uncharacterized genes that provide the basis for future studies to investigate the molecular basis of symbiotic development as well as chronic pathogenic interactions. IMPORTANCE Soil rhizobial bacteria enter into an ecologically and economically important symbiotic interaction with legumes, in which they differentiate into physiologically distinct bacteroids that provide essential ammonia to the plant in return for carbon sources. Plant signal peptides are essential and specific to achieve these physiological changes. These peptides show similarity to mammalian defensin peptides which are part of the first line of defense to control invading bacterial populations. A number of these legume peptides are indeed known to possess antimicrobial activity, and so far, only the bacterial BacA protein is known to protect rhizobial bacteria against their antimicrobial action. This study identified numerous additional bacterial factors that mediate protection and belong to diverse biological pathways. Our results significantly contribute to our understanding of the molecular roles of bacterial factors during legume symbioses and, second, provide insights into the mechanisms that pathogenic bacteria may use to resist the antimicrobial effects of defensins during infections.

Interaction between variants in CLU and MS4A4E modulates Alzheimer's disease risk

Ebbert et al. reported gene‐gene interactions between rs11136000‐rs670139 (CLU‐MS4A4E) and rs3865444‐rs670139 (CD33‐MS4A4E). We evaluate these interactions in the largest data set for an epistasis study.

Fine-mapping of the human leukocyte antigen locus as a risk factor for Alzheimer disease: A case-control study

Background Alzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations. Methods and findings Building on prior work linking the HLA to AD, we used a robust imputation method on two separate case–control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999–2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer’s Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984–2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005–2007 and longitudinal cognitive data from the Alzheimer’s Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10−4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08–1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01–1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01–1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer’s Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = −0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes. Conclusions We provide evidence that variation in the HLA locus—including risk haplotype DR15—contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.

Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments

We sought to determine whether a systems biology approach may identify novel late‐onset Alzheimers disease (LOAD) loci.

Variant Tool Chest: an improved tool to analyze and manipulate variant call format (VCF) files

BackgroundSince the advent of next-generation sequencing many previously untestable hypotheses have been realized. Next-generation sequencing has been used for a wide range of studies in diverse fields such as population and medical genetics, phylogenetics, microbiology, and others. However, this novel technology has created unanticipated challenges such as the large numbers of genetic variants. Each caucasian genome has more than four million single nucleotide variants, insertions and deletions, copy number variants, and structural variants. Several formats have been suggested for storing these variants; however, the variant call format (VCF) has become the community standard.ResultsWe developed new software called the Variant Tool Chest (VTC) to provide much needed tools to work with VCF files. VTC provides a variety of tools for manipulating, comparing, and analyzing VCF files beyond the functionality of existing tools. In addition, VTC was written to be easily extended with new tools.ConclusionsVariant Tool Chest brings new and important functionality that complements and integrates well with existing software. VTC is available at https://github.com/mebbert/VariantToolChest

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease

Background Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). Methods and Findings We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Conclusions Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.

FINE-MAPPING OF THE HUMAN LEUKOCYTE ANTIGEN (HLA) LOCUS AS A RISK FACTOR FOR ALZHEIMER'S DISEASE

angiopathy (CAA) and APP variants or duplications (Nicolas G et al. Mutation in the 3’untranslated region of APPas a genetic determinant of cerebral amyloid angiopathy. European Journal of Human Genetics 2016; 24: 92–98). Nicolas et al. identified APP 3’UTR (3’untranslated region of APP) sequence variants including c.*18C>T as possible genetic determinants of CAA. Methods:This is the case of a 51-year-old female patient with an APP 3’UTR sequence variant, admitted to the clinic due to depressive symptoms. After full remission of the severe depressive episode (ICD10), the patient still suffered from cognitive impairment. Brain MRI-scan revealed frontal lobe atrophy. Electroencephalogram was normal. Neuropsychological assessments showed moderate impairment in tasks on recall of nonverbal visuospatial information as well as in the ability to learn new task rules and slight impairment in tasks on delayed recall of verbal information. FDG-positronemission-tomography and cerebrospinal fluid analysis including beta-amyloid and tau-protein were unremarkable. Due to these conflicting findings and to the patient’s relatively young age, genetic DNA analysis was conducted. Results:Genetic DNA analysis led to detection of the heterozygous APP 3’UTR sequence variant c.*18C>T, so far of unknown significance and with a minor allele frequency of less than 0.01%. No radiological signs of cerebral amyloid angiopathy were found in this patient. She had no family history of psychiatric diseases and was currently diagnosed with mild cognitive impairment, not meeting the criteria for dementia (yet). Conclusions:Thorough follow-up examinations including frequent evaluations of vascular risk factors are necessary to detect early signs of CAA in this patient and to reduce her risk of brain hemorrhage. The reported APP 3’UTR sequence variant could be a genetic determinant of the development of cognitive impairment, possibly of Alzheimer’s disease. Further research and longitudinal studies are necessary to test this hypothesis and to also examine if this variant is a genetic determinant of CAA.

Associations between potentially modifiable risk factors and Alzheimer's disease: A Mendelian random

Background Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). Methods and Findings We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62–0.91]; p = 3.4 × 10−3). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10−8). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89]; p = 6.5 × 10−3), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Conclusions Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.