ACADS Human

What is the ACADS gene and its encoded protein?

The ACADS gene encodes a tetrameric mitochondrial flavoprotein that belongs to the acyl-CoA dehydrogenase family . This gene spans approximately 13 kb in length and contains 10 exons, with a coding sequence of 1239 bp . The resulting protein consists of 412 amino acids and has a molecular weight of 44.3 kDa in humans (44.9 kDa in mice) . The enzyme catalyzes the initial step of the mitochondrial fatty acid beta-oxidation pathway, specifically acting on short-chain fatty acids between C2 and C3-acylCoA . Understanding this basic structure is essential for research design involving ACADS mutations or functional studies.

How does SCAD enzyme function in human metabolism?

The SCAD enzyme catalyzes the first part of fatty acid beta-oxidation by forming a C2-C3 trans-double bond in fatty acids through dehydrogenation of the flavoenzyme . This enzyme exhibits specificity for short-chain fatty acids, particularly those between C2 and C3-acylCoA . The ultimate product of this pathway is acetyl-CoA, which enters the citric acid cycle for energy production . When SCAD is misfolded due to genetic variants, increased production of reactive oxygen species (ROS) can occur, leading to mitochondrial fission and changing the mitochondrial reticulum to a grain-like structure . This understanding provides the biochemical foundation for investigating metabolic consequences of ACADS variants.

What is Short-chain acyl-coenzyme A dehydrogenase deficiency (SCADD)?

SCADD, also known as butyryl-CoA dehydrogenase deficiency, is a metabolic condition associated with mutations in the ACADS gene . Historically considered a metabolic disorder, recent research challenges this classification . A comprehensive study in the BioMe Biobank found that clinically relevant ACADS variants were not associated with evidence of metabolic disease in a large, ancestrally diverse adult population . These findings support the assertion that SCADD may be more of a biochemical entity without clinical correlates, particularly when caused by common variants . When designing studies involving SCADD patients, researchers should consider this nuanced understanding of the condition's clinical significance.

How should researchers design studies to investigate ACADS variants?

When designing studies to investigate ACADS variants, researchers should implement a comprehensive approach that combines genomic analysis with clinical data. As demonstrated in the BioMe Biobank study, researchers utilized exome sequence data linked to electronic health records (EHRs) to identify clinically relevant variants and estimate their prevalence and clinical implications . This methodology allowed for analysis in 27,447 ancestrally diverse and unrelated adults .

For robust study design, researchers should:

• Clearly define variant classification criteria (pathogenic, likely pathogenic, etc.)

• Establish relevant clinical phenotypes based on literature

• Account for population stratification using principal component analysis

• Include demographically diverse participants

• Perform appropriate statistical analyses with adjustments for confounders

The BioMe study extracted ICD-9 and ICD-10 codes corresponding to eight SCADD-associated phenotypes from participants' EHRs, demonstrating a methodologically sound approach to phenotype data collection .

What are best practices for obtaining IRB approval for human subjects research involving ACADS?

When conducting human subjects research involving ACADS, researchers must obtain appropriate Institutional Review Board (IRB) approval. The approval process typically involves several key steps:

• Determine if your project meets the definition of "research" by assessing whether it is a systematic investigation using predetermined methods and is designed to develop or contribute to generalizable knowledge .

• Confirm if your study involves "human subjects" by determining if you will:

  • Acquire information through interaction or intervention with living individuals

  • Obtain identifiable private information about living individuals

  • Involve individuals participating in experimental treatments or procedures

• Complete required human subjects protection training, such as the online training provided by the Office of Human Research Protection (OHRP) .

• Prepare a comprehensive research proposal that includes:

  • Study rationale and objectives

  • Detailed methodology

  • Participant recruitment strategy

  • Data collection and analysis plans

  • Risk assessment and minimization strategies

  • Data security and privacy protection measures

• Develop appropriate informed consent documents that clearly explain study procedures, risks, benefits, and participant rights .

Researchers should submit these materials to their institutional IRB and wait for approval before recruiting subjects or collecting any data .

What methodological approaches are recommended for analyzing ACADS variant prevalence?

For analyzing ACADS variant prevalence, researchers should employ rigorous methodological approaches as demonstrated in recent studies. The BioMe Biobank study provides an exemplary framework:

• Sample Selection and Preparation: Work with an unrelated subset of participants to avoid familial clustering effects. In the BioMe study, researchers restricted their cohort to 27,794 unrelated participants and further refined the sample by excluding individuals with missing demographic data .

• Variant Classification: Clearly define and classify variants of interest (e.g., pathogenic variants [PVs] and common variants [CVs]) .

• Statistical Analysis: Utilize appropriate statistical tests based on data characteristics:

  • Wilcoxon rank-sum test for continuous data that violates normality assumptions

  • Fisher's exact test for categorical variables

  • Multivariate logistic regression to determine associations between variants and phenotypes of interest

• Population Stratification: Account for genetic ancestry using principal component analysis to control for population stratification effects .

• Comprehensive Reporting: Present prevalence data with confidence intervals and stratify by relevant demographic or ancestral groups when sample size permits .

This methodological approach allows for robust prevalence estimates and facilitates comparison across different studies and populations.

How should researchers interpret conflicting findings regarding ACADS clinical significance?

The interpretation of conflicting findings regarding ACADS clinical significance requires a nuanced approach. The BioMe Biobank study revealed that the prevalence of clinically relevant ACADS variants in an unselected population was much higher (approximately 1 in 10,000 for homozygous rare pathogenic variants) than previously reported SCADD prevalence of 1 in 35,000 in the United States . Despite this higher prevalence, individuals with these variants showed no evidence of metabolic disease .

To interpret such conflicts, researchers should:

• Consider ascertainment bias: Earlier studies may have focused on clinically referred populations, leading to overestimation of disease penetrance.

• Evaluate study methodology: Assess differences in variant classification criteria, phenotype definitions, and statistical approaches.

• Analyze population differences: Consider whether discrepancies might reflect true population-specific effects.

• Incorporate functional studies: When possible, include in vitro or in vivo functional studies to validate variant pathogenicity.

• Apply Bayesian frameworks: Update prior probabilities of pathogenicity based on new evidence.

What approaches are recommended for investigating ACADS variants across diverse populations?

Investigating ACADS variants across diverse populations requires methodologically sound approaches to ensure valid cross-population comparisons. The BioMe Biobank study provides a model by including individuals identifying as European American, African/African-American, East/Southeast Asian, Hispanic/Latin American, South Asian, Native American, and individuals of multiple ancestries .

Recommended approaches include:

• Inclusive recruitment strategies: Develop culturally sensitive recruitment approaches to ensure adequate representation of diverse populations.

• Ancestry determination: Implement both self-reported race/ethnicity data and genetic ancestry estimation via principal component analysis .

• Population-specific variant analysis: Assess variant frequencies and clinical correlations within each ancestral group when sample sizes permit.

• Interaction analysis: Evaluate potential interaction effects between ACADS variants and genetic ancestry, as attempted in the BioMe study .

• Context-specific interpretation: Consider environmental, dietary, and cultural factors that may influence phenotypic expression of variants in different populations.

This comprehensive approach helps address the historical underrepresentation of non-European populations in genetic research, as highlighted by the ACAD study's observation that "Asian Americans are still underrepresented in AD studies, in particular genetic studies" . While this referred to Alzheimer's Disease research, the principle applies equally to ACADS research.

What statistical approaches are most appropriate for analyzing associations between ACADS variants and clinical outcomes?

When analyzing associations between ACADS variants and clinical outcomes, researchers should employ robust statistical approaches tailored to genetic association studies. The BioMe Biobank study exemplifies several best practices:

• Multivariate logistic regression: This method allows for assessment of associations while controlling for relevant covariates. In the BioMe study, researchers adjusted for "population group, age, sex, and the first five principal components of ancestry" .

• Composite and individual phenotype analysis: Consider analyzing both a composite outcome (any SCADD-associated phenotype) and individual phenotypes separately .

• Interaction testing: Assess for potential interaction effects, particularly between genotype and population group .

• Appropriate exclusions: Consider excluding carriers (heterozygotes) when focusing on recessive conditions to compare homozygotes with non-carriers .

• Manual chart review: For rare genotype groups with small sample sizes that preclude meaningful statistical analysis, conduct manual chart reviews to assess clinical outcomes qualitatively .

• Power calculations: Conduct a priori power calculations to determine if sample sizes are adequate for detecting clinically meaningful associations.

These approaches help ensure that statistical analyses are appropriate for the data structure and research questions while minimizing the risk of spurious associations.

How are ACADS variants classified and what is their prevalence in research populations?

The classification and prevalence of ACADS variants in research populations provide important context for study design and interpretation. Based on data from the BioMe Biobank study, the following prevalence rates were observed:

Among 2,035 variant-positive individuals in the BioMe study, none had a documented diagnosis of SCADD, including the five PV/PV positive individuals who underwent manual chart review . The CV/CV positive and CV/PV positive individuals did not show increased odds of any of the eight ACADS phenotypes evaluated compared to variant-negative individuals .

For research design purposes, it's important to note that these prevalence rates are higher than previously reported SCADD prevalence of 1 in 35,000 in the United States, suggesting that most individuals with clinically relevant ACADS variants do not develop clinical manifestations of SCADD .

What are the most promising future research directions for ACADS human studies?

Based on current evidence and knowledge gaps, several promising research directions for ACADS human studies include:

• Functional characterization of variants: Further investigation into the molecular mechanisms by which specific ACADS variants affect enzyme function and mitochondrial metabolism.

• Environmental and genetic modifiers: Exploration of potential genetic and environmental factors that might modify the penetrance and expressivity of ACADS variants.

• Longitudinal studies: Long-term follow-up of individuals with clinically relevant ACADS variants to assess potential late-onset manifestations or subtle phenotypes not captured in cross-sectional studies.

• Multi-omics approaches: Integration of genomics with proteomics, metabolomics, and other -omics data to provide a more comprehensive understanding of ACADS variants' effects.

• Targeted functional studies: Investigation of the role of ACADS in specific tissues and metabolic conditions beyond its known role in fatty acid metabolism.

• Therapeutic implications: Exploration of whether individuals with certain ACADS variants might respond differently to medications or dietary interventions affecting mitochondrial function.