Energy Expenditure

Energy expenditure refers to the total amount of energy (calories) the body uses to perform all its functions over a given period. This fundamental biological process is crucial for maintaining life and is broadly divided into three main components: basal metabolic rate (BMR), which accounts for the energy needed to sustain basic bodily functions at rest; the thermic effect of food (TEF), which is the energy expended during the digestion, absorption, and storage of nutrients; and activity energy expenditure (AEE), which comprises the energy used for physical activity, ranging from light movement to strenuous exercise. The balance between energy intake (from food) and energy expenditure dictates changes in body weight and overall metabolic health.^[1]

Biological Basis

The regulation of energy expenditure is a complex physiological process involving intricate interactions between genetic, hormonal, and neural systems. The central nervous system, particularly the hypothalamus, plays a key role in integrating signals related to energy status and modulating energy expenditure. Genetic factors are known to contribute significantly to individual variations in metabolic rates and activity levels, influencing how efficiently the body utilizes or stores energy. Research has identified specific genetic variants associated with different aspects of energy expenditure. For instance, single nucleotide polymorphisms (SNPs) in genes such as_MATK_(megakaryocyte-associated tyrosine kinase) have been linked to total energy expenditure, while variants in_CHRNA3_(cholinergic receptor, neuronal nicotinic, alpha polypeptide 3) are associated with sleeping energy expenditure._CHRNA3_is involved in signal transmission and can activate neurons that regulate energy intake and expenditure through melanocortin-4 receptors. Additionally, an intronic variant in_ARHGAP11A_has been associated with sleep duration, which in turn can affect weight and energy expenditure patterns.^[2]

Clinical Relevance

Understanding energy expenditure is critically important for clinical health, particularly in the context of weight management and the prevention and treatment of metabolic diseases. An imbalance where energy intake consistently exceeds expenditure leads to positive energy balance and can result in overweight and obesity. Obesity is a significant public health concern, linked to numerous comorbidities such as type 2 diabetes, cardiovascular disease, and certain cancers.^[2]Individual differences in energy expenditure, partly influenced by genetics, can explain why some individuals are more susceptible to weight gain than others, even with similar dietary habits. Tailoring interventions, including dietary recommendations and physical activity programs, based on an individual’s specific energy expenditure profile can lead to more effective and personalized health outcomes.

Social Importance

The societal impact of energy expenditure is far-reaching, primarily due to its central role in the global obesity epidemic. Rising rates of obesity impose substantial burdens on healthcare systems and national economies. Public health initiatives often focus on promoting increased physical activity and balanced diets, which directly aim to influence energy expenditure and intake. Research into the genetic and environmental determinants of energy expenditure contributes to a deeper understanding of metabolic health and can inform more effective public health strategies. By identifying individuals at higher genetic risk for lower energy expenditure or those who respond differently to lifestyle interventions, more targeted prevention and treatment programs can be developed, potentially mitigating the social and economic costs associated with obesity and related conditions.

Methodological and Statistical Considerations

The study’s findings are subject to several methodological and statistical limitations inherent to genome-wide association studies (GWAS) and its specific design. The cohort consisted of 815 children from 263 Hispanic families, a sample size that, while substantial, may limit the statistical power to detect all relevant genetic variants, particularly those with smaller effect sizes or those that are rare within the population.^[2]Furthermore, the ascertainment strategy, which involved recruiting families based on an obese proband, introduces a potential cohort bias that may impact the generalizability of findings to the broader Hispanic population or to individuals across the entire spectrum of body weight.^[2] The identified genetic variants are considered markers for genomic regions rather than direct causal variants, underscoring the necessity for additional studies to functionally characterize these variants and replicate the associations to confirm their significance.^[2]

Generalizability and Phenotype Specificity

The study was conducted exclusively within a Hispanic pediatric population, which, while providing valuable insights specific to this group, inherently limits the direct generalizability of the findings to other ancestral populations.^[2]The genetic architecture influencing energy expenditure can vary across different ethnic groups, and the genotyping platform used may not fully capture rare variants unique to the Hispanic population, potentially leading to an incomplete understanding of genetic contributions.^[2]Additionally, the measurements of total energy expenditure and sleeping energy expenditure were rigorously adjusted for body weight to account for its strong influence across the wide age range of the cohort.^[2]While this adjustment is crucial for isolating genetic effects on energy expenditure independent of body mass, it means the reported associations pertain to weight-adjusted values, which might complicate direct interpretation of genetic effects on unadjusted energy expenditure or its interplay with body weight itself.

Unexplained Variance and Functional Gaps

Despite identifying several genome-wide significant loci, these variants likely explain only a fraction of the overall variance in energy expenditure and related traits, leaving a considerable portion of heritability unexplained. For instance, a common variant inINADLaccounted for only 3% of the variance in body weight and body composition, illustrating the polygenic nature of such complex traits and the presence of significant “missing heritability”.^[2] The precise biological mechanisms by which many of the identified variants, such as those in CHRNA3associated with sleeping energy expenditure, exert their effects on energy metabolism are often plausible but remain largely uncertain and require further in-depth investigation.^[2]Moreover, while the study acknowledges the role of both genetic and environmental factors in childhood obesity, the intricate interplay between specific genetic variants and various environmental or lifestyle confounders (e.g., diet composition, physical activity patterns beyond measured activity, socioeconomic factors) was not fully elucidated, representing a critical area for future research.

Variants

Genetic variations play a crucial role in shaping an individual’s energy metabolism and predisposition to various metabolic traits. Among these, the variant rs12104221 in the MATKgene has been significantly associated with total energy expenditure, adjusted for body weight, in studies focusing on childhood obesity in Hispanic populations.^[2] MATK encodes a megakaryocyte-associated tyrosine kinase, a protein-tyrosine kinase involved in intracellular signal transduction pathways, suggesting its influence on cellular processes that contribute to overall energy balance.^[3] Concurrently, rs8040868 within the CHRNA3gene, encoding the cholinergic receptor, neuronal nicotinic, alpha polypeptide 3, has shown association with sleeping energy expenditure.^[2]This receptor is part of a superfamily of ligand-gated ion channels that mediate rapid signal transmission at synapses, and its activation by acetylcholine can influence energy metabolism by interacting with proopiomelanocortin (POMC) neurons, which in turn regulate energy intake and expenditure through melanocortin-4 receptors.^[4] Other variants are implicated in pathways affecting energy utilization and metabolic regulation. For instance, the CPT1Agene encodes carnitine palmitoyltransferase 1A, an enzyme essential for the transport of long-chain fatty acids into mitochondria, where they are oxidized to produce energy. Variants likers2924679 can impact the efficiency of this enzyme, thereby influencing the body’s ability to burn fat and potentially affecting overall metabolic rate and susceptibility to conditions like obesity.^[2] Similarly, SMYD3 (SET and MYND domain containing 3) acts as a histone methyltransferase, playing a role in epigenetic regulation of gene expression. The variant rs11800820 might alter its activity, potentially affecting the expression of genes involved in metabolic pathways or adipogenesis.^[2] The S100P gene, encoding S100 calcium-binding protein P, is involved in cellular processes such as proliferation, differentiation, and inflammation. The variant rs3822262 could modulate its function, indirectly influencing energy expenditure through its effects on inflammatory responses or cell signaling relevant to metabolic health.^[2] Further genetic insights point to the involvement of DYNC1I1, MOXD1, and UMAD1 in metabolic phenotypes. DYNC1I1 (dynein cytoplasmic 1 intermediate chain 1) is a component of the dynein motor protein complex, crucial for intracellular transport. The variant rs1488515 could affect the efficiency of these transport mechanisms, potentially impacting the movement of mitochondria or other organelles vital for cellular energy production.^[2] MOXD1 (monooxygenase DBH-like 1) is thought to be involved in monooxygenase activity, which could impact various metabolic processes, including neurotransmitter synthesis or lipid metabolism. The variant rs589756 may alter the enzyme’s function, thus influencing these metabolic pathways.^[2] The role of UMAD1(uveal melanoma associated antigen 1) in energy expenditure is less understood, but its involvement in cellular growth or survival pathways suggests potential indirect effects on metabolic regulation, withrs12702661 possibly modulating these cellular functions.^[2] The genomic region encompassing MPHOSPH6-DT and CDH13 also presents a locus of interest, with rs11863065 potentially influencing metabolic traits. CDH13(Cadherin 13), also known as adiponectin receptor 3, plays a significant role in adiponectin signaling, which is critical for insulin sensitivity, glucose uptake, and overall energy metabolism.^[2] A variant like rs11863065 could affect CDH13expression or function, thereby modulating adiponectin’s metabolic effects. TheMPHOSPH6-DT gene, a pseudogene, may exert regulatory effects on neighboring genes, including CDH13, further influencing metabolic outcomes.^[2] Additionally, the KDM4C gene (lysine demethylase 4C), along with RPL4P5, is associated with rs1887867 . KDM4C is an epigenetic modifier involved in removing methyl groups from histones, which can significantly alter gene expression. This variant could impact the regulation of genes involved in adipogenesis, nutrient sensing, or mitochondrial function, thereby affecting energy balance.^[2]

Key Variants

RS ID	Gene	Related Traits
rs12104221	MATK	energy expenditure
rs8040868	CHRNA3	forced expiratory volume FEV/FVC ratio forced expiratory volume, response to bronchodilator FEV/FVC ratio, response to bronchodilator FEV/FVC ratio, pulmonary function , smoking behavior trait
rs11863065	MPHOSPH6-DT - CDH13	body weight body mass index energy expenditure hip circumference
rs1887867	KDM4C - RPL4P5	energy expenditure
rs1488515	DYNC1I1	energy expenditure
rs589756	MOXD1	lean body mass energy expenditure maximal oxygen uptake waist circumference body weight
rs12702661	UMAD1	energy expenditure
rs3822262	S100P	energy expenditure
rs11800820	SMYD3	energy expenditure
rs2924679	CPT1A	energy expenditure

Defining Energy Expenditure and its Role in Energy Balance

Energy expenditure refers to the total amount of energy, typically quantified in calories, utilized by an organism to sustain life processes, engage in physical activities, and digest and absorb nutrients.^[2]It is a critical component of energy balance, where an imbalance between energy intake and expenditure is a primary factor underlying the development of conditions such as childhood obesity.^[1]Conceptually, energy expenditure is integral to the central control of energy balance, a complex physiological system influenced by both genetic predispositions for efficient energy storage and environmental factors like food availability and sedentary behaviors.^[5]Understanding this trait is essential for identifying biological processes and causal genetic variants related to obesity pathophysiology.^[2]

Components and Classification of Energy Expenditure

Energy expenditure can be broadly classified into several key components that reflect different physiological states and activities. Total energy expenditure (TEE) represents the sum of all energy expended over a given period, while sleeping energy expenditure specifically quantifies the energy used during periods of rest.^[2]Activity energy expenditure, another significant component, accounts for the energy utilized during physical movement.^[6]These components are often considered in relation to the estimated energy requirement (EER), a benchmark for energy intake, especially when analyzing dietary consumption in research settings.^[2]For accurate assessment and analysis, especially in research, energy expenditure measures are frequently adjusted to account for confounding variables. Total energy expenditure and sleeping energy expenditure, for instance, are strongly influenced by body weight and are thus adjusted for this factor across various age ranges.^[2] Furthermore, comprehensive adjustments for age, sex, their interaction, and higher-order terms are routinely applied to normalize phenotypes and meet statistical assumptions in genetic analyses.^[2]This meticulous approach ensures that observed variations in energy expenditure are not merely reflections of demographic or anthropometric differences.

Methodologies and Genetic Modulators

Precise of energy expenditure is crucial for both clinical assessment and scientific research, employing a range of sophisticated methodologies. The doubly labeled water method is a gold standard for determining total energy expenditure in free-living individuals, offering robust estimates over several days.^[7]For controlled, detailed 24-hour measurements of energy expenditure and substrate oxidation, room respiration calorimetry is utilized, providing comprehensive metabolic data.^[2]Additionally, activity energy expenditure can be estimated using accelerometers, such as Actiwatch devices, which quantify the frequency, duration, and intensity of physical activity.^[6]Genetic studies have begun to unravel the molecular underpinnings of variations in energy expenditure, identifying specific loci associated with its different components. For example, total energy expenditure, adjusted for body weight, has been significantly associated with the variantrs12104221 in the MATK gene, which encodes a protein-tyrosine kinase involved in signal transduction pathways.^[2]Similarly, sleeping energy expenditure, also adjusted for body weight, shows an association withrs8040868 in CHRNA3 (cholinergic receptor, nicotinic, alpha 3), a gene for a ligand-gated ion channel that mediates fast signal transmission at synapses.^[2]This variant suggests a plausible role in energy metabolism, potentially by activating proopiomelanocortin (POMC) neurons that subsequently activate melanocortin-4 receptors, both critical for regulating energy intake and expenditure.^[2] Other variants, such as those in ARHGAP11A for sleep duration and CTCFLfor sedentary-light physical activity, also highlight the complex genetic architecture influencing energy balance.^[2]

Biological Background

Energy expenditure is a fundamental physiological process representing the total amount of energy consumed by the body to maintain vital functions, support physical activity, and process food. This complex trait is tightly regulated by intricate networks involving molecular pathways, genetic factors, and systemic physiological responses, all of which contribute to an individual’s overall energy balance. Disruptions in this balance can lead to various pathophysiological conditions, notably obesity, where energy intake consistently exceeds expenditure.^[1]Understanding the biological underpinnings of energy expenditure is crucial for deciphering the mechanisms of metabolic health and disease.

Neural and Hormonal Control of Energy Balance

The central nervous system plays a pivotal role in regulating energy expenditure through complex signaling pathways involving key neurotransmitters and receptors. For instance, the cholinergic system, mediated by acetylcholine, is deeply implicated in energy metabolism. Specifically, the neuronal cholinergic receptor, nicotinic, alpha polypeptide 3 (CHRNA3), a member of the ligand-gated ion channel superfamily, facilitates rapid signal transmission at synapses.^[2] Upon binding acetylcholine, CHRNA3 opens ion-conducting channels across the plasma membrane, influencing neuronal excitability.^[8] This activation extends to proopiomelanocortin (POMC) neurons, which subsequently activate melanocortin-4 receptors (MC4R). The MC4Rsystem is a critical regulator of both energy intake and expenditure, highlighting how neural signaling cascades involving biomolecules like acetylcholine and receptors such asCHRNA3 and MC4R contribute to systemic energy homeostasis.^[4] Genetic variants, such as rs8040868 in CHRNA3, can therefore impact sleeping energy expenditure by modulating these neural pathways.^[2]

Cellular Signaling and Metabolic Regulation

Beyond neural control, cellular signaling pathways, particularly those involving protein kinases, are central to the regulation of energy expenditure at a more granular level. The megakaryocyte-associated tyrosine kinase (MATK) is a critical protein-tyrosine kinase involved in various signal transduction pathways within cells.^[3] Tyrosine kinases act as molecular switches, phosphorylating specific proteins to initiate or modulate diverse cellular functions, including metabolism, growth, and differentiation. A variant like rs12104221 in MATKhas been associated with total energy expenditure, suggesting that subtle alterations in these fundamental cellular signaling processes can have systemic consequences on how the body utilizes energy.^[2]These molecular mechanisms govern the efficiency of metabolic processes, impacting everything from basal metabolic rate to the energy cost of thermogenesis and nutrient processing, ultimately contributing to the overall energy balance of an organism.

Genetic and Epigenetic Modulators of Energy-Related Behaviors

Genetic and epigenetic mechanisms profoundly influence behaviors that contribute to energy expenditure, such as sleep patterns and physical activity. Sleep duration, a key determinant of daily energy balance, is influenced by genes likeARHGAP11A (Rho GTPase activating protein 11A), where an intronic variant (rs17104363 ) has been associated with sleep duration.^[2] This gene encodes a protein with a rhoGAP domain, suggesting its involvement in cellular signaling pathways that may affect sleep regulation.^[2] The clinical relevance is underscored by the observation that sleep disturbances are characteristic of Prader-Willi Syndrome, a condition linked to a deletion encompassing ARHGAP11A, and emerging evidence suggests a bidirectional relationship between obesity and sleep patterns.^[9]Furthermore, physical activity levels, particularly sedentary-light activity, are influenced by genes such asCTCFL, an 11-zinc-finger factor involved in gene regulation.^[2] CTCFL forms methylation-sensitive insulators, which are epigenetic regulatory elements that control gene expression by influencing chromatin structure.^[10]Such epigenetic modifications can alter the expression patterns of genes involved in metabolic or behavioral processes, thereby modulating an individual’s propensity for physical activity and, consequently, their energy expenditure.

Integrated Systems Physiology and Pathophysiology of Energy Imbalance

The integration of molecular, cellular, and genetic mechanisms orchestrates the complex physiological trait of energy expenditure, with systemic consequences for health and disease. Total energy expenditure is a composite measure reflecting basal metabolic rate, thermic effect of food, and physical activity, all of which are subject to multi-level regulation. Genetic variants in genes likeMATK and CHRNA3can subtly alter key signaling pathways or neuronal functions, leading to variations in total and sleeping energy expenditure among individuals.^[2] When these regulatory systems are disrupted, such as through genetic predispositions affecting MC4Rfunction or sleep-related genes, the delicate balance between energy intake and expenditure can be perturbed, contributing to pathophysiological processes like childhood obesity.^[11] The identified genetic variants, while often markers for broader genomic regions, highlight specific biological pathways that warrant further investigation to fully understand their functional role in the etiology of complex metabolic disorders and the development of targeted interventions.^[2]

Neuroendocrine Control of Energy Expenditure

The regulation of energy expenditure involves intricate neuronal signaling pathways that integrate environmental cues with internal metabolic states. For instance, the cholinergic receptor, neuronal nicotinic, alpha polypeptide 3 (CHRNA3), a ligand-gated ion channel, plays a crucial role in regulating sleeping energy expenditure. Upon binding to acetylcholine, this receptor initiates fast signal transmission at synapses by opening ion-conducting channels across the plasma membrane.^[8]This activation then triggers proopiomelanocortin (POMC) neurons, which subsequently activate melanocortin-4 receptors, central components in the broader regulation of both energy intake and expenditure.^[4] This cascade highlights a direct neuroendocrine pathway through which specific receptor activation translates into systemic metabolic control.

Intracellular Signal Transduction and Metabolic Homeostasis

Beyond neuronal signaling, intracellular signal transduction pathways are vital for modulating cellular energy processes and overall metabolic homeostasis. The megakaryocyte-associated tyrosine kinase (MATK), for example, encodes a protein-tyrosine kinase involved in these critical signal transduction pathways.^[3] Variants in MATKhave been significantly associated with total energy expenditure, suggesting its role in the cellular machinery that processes and utilizes energy. Furthermore, proteins likeINADL, which contains PDZ domains and is implicated in adipocyte differentiation, contribute to metabolic regulation by influencing the formation and function of adipocytes, thus affecting energy storage and release.^[12] These pathways underscore the importance of precise molecular signaling in maintaining metabolic balance.

Genetic Regulation of Activity and Sleep Patterns

Gene regulation and protein modification mechanisms profoundly influence daily physical activity and sleep, both of which are critical determinants of energy expenditure. A variant inCTCFL(CCCTC-binding factor (zinc finger protein)-like), an 11-zinc-finger factor, is associated with sedentary-light physical activity and is involved in gene regulation, including the formation of methylation-sensitive insulators.^[10] Similarly, ARHGAP11A (rho GTPase activating protein 11A), which possesses a rhoGAP domain and a tyrosine phosphorylation site, is associated with sleep duration.^[9]Sleep patterns are increasingly recognized as influencing body weight, and disturbances in sleep are a characteristic feature of conditions like Prader Willi Syndrome, a disorder involving a deletion encompassingARHGAP11A.^[13] These regulatory mechanisms highlight how genetic factors influence behavioral and physiological aspects that impact energy balance.

Integrated Systems and Disease-Relevant Mechanisms

Energy expenditure is not governed by isolated pathways but through a complex, integrated system with significant implications for disease. The interplay of various genetic loci, such as those influencing physical activity and dietary intake, contribute to the overall energy balance.^[14]Dysregulation within these pathways can lead to conditions like childhood obesity, which is often rooted in an underlying energy imbalance.^[1] Moreover, systemic processes like inflammation can interact with energy metabolism; variants in the ABO gene, which determines blood group, are associated with fasting serum IL-6 levels, an inflammatory marker.^[15] While the precise mechanism by which ABOalleles affect these biomarkers and their direct link to energy expenditure is still under investigation, these associations point to a broader network where systemic inflammation may influence metabolic health and contribute to the pathophysiology of obesity.

Genetic Insights into Metabolic Regulation

Understanding the genetic underpinnings of energy expenditure is crucial for deciphering individual variations in metabolism and susceptibility to metabolic disorders. Research has identified specific genetic variants associated with both total energy expenditure and sleeping energy expenditure, providing insights into the complex biological pathways involved. For instance, a variant inMATK (rs12104221 ) has been linked to total energy expenditure, withMATK encoding a protein-tyrosine kinase implicated in signal transduction pathways.^[2] Similarly, a variant in CHRNA3 (rs8040868 ), which codes for a cholinergic receptor, is associated with sleeping energy expenditure, suggesting a role in neural signaling that mediates energy metabolism, potentially through its activation of proopiomelanocortin neurons that regulate energy intake and expenditure.^[2]These findings highlight how genetic predispositions can influence fundamental metabolic rates, thereby contributing to the pathophysiology of conditions like childhood obesity.^[2]

Energy Expenditure in Obesity Risk and Personalized Interventions

The genetic influence on energy expenditure has significant implications for risk stratification and the development of personalized medicine approaches, particularly in populations at high risk for obesity, such as Hispanic children. Identifying individuals with genetic variants that predispose them to lower energy expenditure can flag them for early, targeted interventions. Such genetic insights facilitate a shift from generalized public health recommendations to more precise, personalized prevention strategies that consider an individual’s unique metabolic profile.^[2]This tailored approach can optimize lifestyle modifications, including diet and physical activity, to counteract genetic predispositions and mitigate the risk of developing obesity and its associated complications.^[1]

Clinical Monitoring, Prognosis, and Comorbidities

Measuring energy expenditure, often through methods like 24-hour room calorimetry, serves as a valuable clinical tool for diagnostic utility and monitoring strategies in patients with metabolic conditions.^[2]Deviations in energy expenditure can serve as prognostic indicators for disease progression or responsiveness to therapeutic interventions, offering clinicians objective data to guide treatment selection and evaluate outcomes in conditions like obesity. Furthermore, energy expenditure is intricately linked with various comorbidities and overlapping phenotypes, such as sleep disturbances, where variants in genes likeARHGAP11A are associated with sleep duration, and inflammation markers like MCP-1 and IL-6, which are also genetically influenced and play roles in metabolic regulation.^[2]Understanding these associations allows for a more holistic approach to patient care, addressing the multifaceted nature of obesity and its related complications.

Frequently Asked Questions About Energy Expenditure

These questions address the most important and specific aspects of energy expenditure based on current genetic research.

---

1. 1: Why can’t I lose weight even when my friend eats more than me?

Your body’s energy expenditure is highly individual, partly due to genetics. You and your friend might have different genetic variants influencing your metabolic rates and how efficiently your body uses or stores energy. For instance, variants in genes like MATK have been linked to total energy expenditure, contributing to these personal differences. This means your body might naturally burn fewer calories at rest or during activity.

2. Does staying up late make me gain weight?

Yes, your sleep patterns can significantly impact your energy expenditure and weight. Genetic variants, such as an intronic variant in ARHGAP11A, are associated with sleep duration, which in turn affects your energy use patterns. Additionally, variants in CHRNA3, involved in signal transmission, are linked to sleeping energy expenditure, influencing how many calories you burn while you sleep. Disrupting these patterns can throw off your energy balance.

3. My sibling is thin but I’m not - why the difference?

Even within families, individuals can have different genetic predispositions affecting their energy expenditure. You and your sibling likely inherited different combinations of genetic variants that influence your metabolic rates, how your body stores fat, or even your activity levels. While lifestyle plays a huge role, these subtle genetic differences can make one person more susceptible to weight gain than another.

4. I’m Hispanic - does my background affect my weight risk?

Yes, research suggests that the genetic factors influencing energy expenditure can vary across different ethnic groups. Studies, particularly in Hispanic populations, have identified specific genetic variants that may contribute to differences in metabolic health and susceptibility to obesity within this group. Understanding these unique genetic architectures is important for personalized health strategies.

5. Can exercise really overcome bad family history?

While genetic factors significantly contribute to your metabolic rate and susceptibility to weight gain, consistent lifestyle choices like exercise and a balanced diet are incredibly powerful. Even if you have a genetic predisposition, regular physical activity can increase your activity energy expenditure and improve your overall metabolic health. These efforts can often mitigate genetic risks and help manage your weight effectively.

6. Why do some people never gain weight no matter what they eat?

Some individuals naturally have a higher energy expenditure or a more efficient metabolism, which is partly determined by their genetics. They may possess genetic variants that lead to a higher basal metabolic rate, meaning their bodies burn more calories even at rest. This allows them to maintain a stable weight more easily, even with seemingly higher calorie intake, compared to others.

7. Is a DNA test actually worth it for weight problems?

Genetic tests can offer insights into your predispositions by identifying specific variants linked to aspects of energy expenditure, like those affecting your metabolism or sleep. For example, variants in CHRNA3 are linked to sleeping energy expenditure. However, these identified variants typically explain only a small fraction of overall weight variance, as traits like body weight are highly polygenic. Personalized lifestyle interventions remain key, but genetic information can help tailor recommendations.

8. Does stress actually cause weight gain or is that a myth?

While the direct link to specific genes wasn’t detailed in the context of stress, the central nervous system, particularly the hypothalamus, plays a critical role in integrating signals related to energy status and modulating energy expenditure. Chronic stress can influence these neural and hormonal systems, potentially altering your metabolism and energy balance. Such changes can indirectly contribute to weight gain.

9. Is it true that metabolism slows down as you age?

Yes, metabolism, which is a key component of energy expenditure, generally tends to slow down with age. This is often due to a combination of factors, including a natural decline in muscle mass, which burns more calories than fat, and hormonal changes. Understanding your energy expenditure profile becomes increasingly important as you get older to adapt your lifestyle and maintain a healthy weight.

10. Why do weight loss diets work for others but not me?

Your individual response to weight loss diets is significantly influenced by your unique genetic makeup and how your body processes energy. Some people have genetic variations that affect their metabolic rate or how efficiently their bodies store or utilize nutrients. This can mean that a diet effective for one person might not be as effective for you, highlighting the need for personalized dietary approaches.

---

This FAQ was automatically generated based on current genetic research and may be updated as new information becomes available.

Disclaimer: This information is for educational purposes only and should not be used as a substitute for professional medical advice. Always consult with a healthcare provider for personalized medical guidance.

References

[1] Butte, N. F., Christiansen, E., & Sorensen, T. I. “Energy Imbalance Underlying the Development of Childhood Obesity.”Obesity, vol. 15, no. 12, 2007, pp. 3056-3066.

[2] Comuzzie, A. G. “Novel Genetic Loci Identified for the Pathophysiology of Childhood Obesity in the Hispanic Population.”PLoS One, vol. 7, no. 12, 2012, e51954.

[3] Bennett, B. D., et al. “Identification and characterization of a novel tyrosine kinase from megakaryocytes.” Journal of Biological Chemistry, vol. 269, no. 2, 1994, pp. 1068-1074.

[4] Mineur, Y. S., et al. “Nicotine Decreases Food Intake Through Activation of POMC Neurons.” Science, vol. 332, 2011, p. 1330.

[5] O’Rahilly, S., and I. S. Farooqi. “Human Obesity as a Heritable Disorder of the Central Control of Energy Balance.”Int J Obes (Lond), vol. 32, suppl. 7, 2008, pp. S55-S61.

[6] Puyau, M. R., et al. “Prediction of Activity Energy Expenditure Using Accelerometers in Children.”Med Sci Sports Exerc, vol. 36, 2004, pp. 1625–1631.

[7] Johnson, R. K., et al. “Comparison of Multiple-Pass 24-Hour Recall Estimates of Energy Intake with Total Energy Expenditure Determined by the Doubly Labeled Water Method in Young Children.”J Am Diet Assn, vol. 96, 1996, pp. 1140–1144.

[8] Woolf, N. J., and L. L. Butcher. “Cholinergic systems in the rat brain: III. Projections from the pontomesencephalic tegmentum to the thalamus, tectum, basal ganglia, and basal forebrain.” Brain Research Bulletin, vol. 16, no. 5, 1986, pp. 603–637.

[9] Kelly-Pieper, K., et al. “Sleep and obesity in children: a clinical perspective.”Minerva Pediatrica, vol. 63, no. 6, 2011, pp. 473–481.

[10] Klenova, Elena M., et al. “The novel BORIS+CTCF gene family is uniquely involved in the epigenetics of normal biology and cancer.”Seminars in Cancer Biology, vol. 12, no. 5, 2002, pp. 399–414.

[11] Cole, Shelley A., et al. “Evidence that multiple genetic variants of MC4Rplay a functional role in the regulation of energy expenditure and appetite in Hispanic children.”American Journal of Clinical Nutrition, vol. 91, no. 1, 2010, pp. 191–198.

[12] Zhong, Jin, et al. “Temporal profiling of the secretome during adipogenesis in humans.” Journal of Proteome Research, vol. 9, no. 10, 2010, pp. 5228–5238.

[13] Torrado, M., et al. “Clinical-etiologic correlation in children with Prader-Willi syndrome (PWS): an interdisciplinary study.” American Journal of Medical Genetics Part A, vol. 143, no. 5, 2007, pp. 460–468.

[14] Cai, G., et al. “Genome-Wide Scan Revealed Genetic Loci for Energy Metabolism in Hispanic Children and Adolescents.” International Journal of Obesity, vol. 32, no. 4, 2008, pp. 579-585.

[15] Naitza, Silvia, et al. “A genome-wide association scan on the levels of markers of inflammation in Sardinians reveals associations that underpin its complex regulation.” PLoS Genetics, vol. 8, no. 1, 2012, e1002480.