DATE: May 23, 2025 at 06:00PM
SOURCE: PSYPOST.ORG

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TITLE: Judgments of breast attractiveness show surprising consistency across gender, race, and orientation

URL: https://www.psypost.org/judgments-of-breast-attractiveness-show-surprising-consistency-across-gender-race-and-orientation/

People from different demographic backgrounds tend to agree on what they consider attractive when it comes to breast aesthetics, according to a new study published in the Journal of Plastic, Reconstructive & Aesthetic Surgery. While small differences were observed based on gender, sexual orientation, and race, the patterns of preference were strongly correlated across all groups, suggesting some consistency in aesthetic judgments.

The study was designed to explore how different demographic groups perceive breast attractiveness. In recent years, there has been growing awareness that aesthetic ideals may not be universally held, and that factors like race, gender identity, and sexual orientation can shape beauty standards.

In plastic and reconstructive surgery, understanding these nuances has become increasingly important, especially when guiding patients through aesthetic decisions. While earlier work has proposed objective formulas for the “ideal” breast, such as certain volume ratios or nipple positions, this study asked whether preferences really are shared equally across groups.

To answer this question, the research team assembled a set of 25 pre-surgical photographs of patients who had presented for breast surgery at a plastic surgery clinic. These photographs, taken from a front-facing view and cropped to focus only on the torso area, included a diverse range of breast sizes, shapes, skin tones, and nipple-areola configurations. Patients had not undergone prior breast procedures, and all had given consent for their images to be used in de-identified research. About half of the patients were White or Caucasian, with others identifying as Asian, Black or African American, or Hispanic.

The researchers then created an online survey using the Qualtrics platform, distributing the images to a demographically representative sample of the United States population. Participants were asked to rate each pair of breasts on a five-point Likert scale, ranging from “least attractive” to “most attractive.” In addition to these ratings, respondents provided demographic information, including their sex, gender identity, race, and sexual orientation. In total, 1,021 people completed the survey, with a nearly even split between men and women.

The findings revealed several patterns. On average, male participants rated breasts as more attractive than female participants did, giving an average rating of 2.8 compared to 2.5 on the five-point scale. Although men gave higher scores overall, their preferences were still strongly correlated with those of women. In other words, both sexes tended to agree on which breasts were more or less attractive, even if men were more generous with their scores.

A similar pattern appeared when analyzing responses based on sexual orientation. People who reported being attracted to women gave higher ratings across the board than those attracted only to men. Those who were attracted to both men and women gave ratings comparable to respondents attracted only to women and significantly higher than those only attracted to men. This suggests that attraction to women may increase the perceived attractiveness of female breasts, regardless of the rater’s own gender.

Racial differences in ratings were more complex. White or Caucasian respondents gave higher average ratings than Asian respondents, with scores of 2.7 and 2.2 respectively. However, the difference between White and Black or African American respondents was not statistically significant. Importantly, across all racial groups, the relative rankings of breast attractiveness were highly correlated. That means that even when one group tended to give lower average ratings, they still agreed with others on which images were more or less attractive.

The study also explored whether people rated breasts from their own racial group more favorably than others. There was no evidence for this kind of in-group bias. For example, White respondents did not give higher ratings to breasts from White patients, nor did Black or Asian respondents favor patients from their own racial group. Three of the five highest-rated breasts belonged to White or Caucasian patients, while one came from a Black or African American patient and one from an Asian patient. This finding suggests that skin tone alone did not drive differences in ratings, although the researchers noted that respondents could still visually perceive differences in skin color in the photographs.

Although the study provides new insight into how people perceive breast aesthetics, it does have several limitations. The sample of photographed patients was relatively small and not fully representative of the racial and ethnic diversity found across the United States. All images came from individuals who visited the same surgeon, and the final selection was made by that surgeon, potentially introducing bias into the photo set.

Another important consideration is that survey participants were not asked why they rated breasts the way they did. Future studies could explore the reasoning behind individual ratings, perhaps by asking participants to comment on specific features like nipple position, breast symmetry, or fullness of the upper and lower pole. New technologies, such as artificial intelligence-generated imagery, might also help future research isolate variables more effectively by creating standardized images that differ in only one feature at a time.

Despite these caveats, the findings suggest that personal identity plays a role in shaping aesthetic preferences. While demographic groups may show different average preferences, the high correlations between them indicate broad agreement on the relative appeal of different breast appearances.

The study, “Differential preferences in breast aesthetics by self-identified demographics assessed on a national survey,” was authored by Carter J. Boyd, Jonathan M. Bekisz, Kshipra Hemal, Thomas J. Sorenson, and Nolan S. Karp.

URL: https://www.psypost.org/judgments-of-breast-attractiveness-show-surprising-consistency-across-gender-race-and-orientation/

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DATE: May 23, 2025 at 04:00PM
SOURCE: PSYPOST.ORG

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TITLE: Neuroscientists challenge “dopamine detox” trend with evidence from avoidance learning

URL: https://www.psypost.org/neuroscientists-challenge-dopamine-detox-trend-with-evidence-from-avoidance-learning/

A new study published in Current Biology sheds light on how the brain learns to avoid harmful situations, revealing that dopamine—commonly associated with pleasure and reward—also plays a flexible and complex role in helping us sidestep danger. Researchers at Northwestern University found that two subregions of the brain’s reward center respond differently to negative experiences, and these responses shift over time as learning progresses. The results suggest that dopamine isn’t just about seeking rewards—it also helps shape our behavior in response to unpleasant experiences, with implications for understanding anxiety, depression, and obsessive-compulsive disorder.

The study was designed to investigate how dopamine contributes to learning from negative experiences, particularly when it comes to avoiding them. While previous research has shown that dopamine can respond to threats or discomfort, it has been unclear how these signals evolve over time and whether they differ by brain region. The research team wanted to understand how the brain adapts when outcomes are predictable and controllable, and how this learning might go awry in psychiatric conditions that involve excessive avoidance behaviors.

To explore these questions, the researchers conducted experiments with mice using a behavioral task designed to measure avoidance learning. Mice were placed in a two-chamber apparatus and given a five-second warning—consisting of a tone and a light—before a mild footshock would be delivered. If the mouse moved to the other chamber during the warning, the shock was avoided. If it stayed put, the shock occurred but stopped as soon as the mouse moved. This setup allowed the team to measure both avoidance and escape behaviors over several days of training.

The researchers recorded dopamine activity in two specific parts of the brain’s reward system: the core and the ventromedial shell of the nucleus accumbens. Using advanced fiber photometry techniques and genetically encoded dopamine sensors, they tracked how dopamine levels changed in response to the warning cue, the shock, and the mouse’s movement across chambers. This allowed them to monitor how learning unfolded over time and how different brain regions contributed to this process.

The results showed that the two brain regions processed aversive learning in distinct ways. In the ventromedial shell, dopamine levels initially surged in response to the shock itself. As the mice began to associate the warning cue with the impending shock, dopamine activity shifted to respond to the cue. But as the animals became more proficient at avoiding the shock, the dopamine response in this region faded. This suggests that the ventromedial shell plays a role in early learning and in identifying when something unpleasant is about to happen.

In contrast, the core of the nucleus accumbens showed a different pattern. Dopamine levels in this area decreased in response to both the warning cue and the shock. As the mice improved at avoiding the shock, the drop in dopamine in response to the cue became stronger. This suggests that the core is involved in refining avoidance behaviors as the animal becomes more skilled. The researchers found that dopamine signals in the core were especially tied to the animal’s actions, suggesting a role in guiding learned movement patterns during avoidance.

These patterns also shifted depending on the controllability of the outcome. After the mice had mastered avoiding the shock, the researchers changed the task so that the shock occurred regardless of the animal’s behavior. Under these conditions, dopamine responses reverted to earlier patterns, indicating that the brain’s learning signals are sensitive to whether a threat can be avoided. This flexibility may be important for helping animals adjust their behavior when the environment changes.

Importantly, the findings help explain why some people may struggle to accurately assess threats or may engage in excessive avoidance, as seen in anxiety and obsessive-compulsive disorders. Alterations in dopamine signaling could lead to exaggerated perceptions of danger, making it harder to adapt when situations change or when risks are no longer present. Understanding these processes could eventually inform treatments for these conditions.

The study also challenges popular ideas about dopamine, including the trend known as the “dopamine detox,” which suggests that avoiding pleasurable activities can reset the brain’s reward system. According to the researchers, this view oversimplifies dopamine’s role. “Dopamine is not all good or all bad,” said Gabriela Lopez, the study’s first author. ‘It rewards us for good things but also helps us tune into cues that signal trouble, learn from consequences and continuously adapt our learning strategies in unstable environments.”

Talia Lerner, the study’s senior author, emphasized that dopamine’s flexibility is key. “These responses are not only different in their sign — where in one area, dopamine goes up for something bad and, in the other area, it goes down for something bad — but we also saw that one is important for early learning while the other one is important for later-stage learning,” she explained.

While the findings are promising, the researchers note that their work was conducted in mice and may not fully translate to humans without further study. In addition, although the researchers monitored a range of behaviors and brain responses, the precise molecular mechanisms behind these patterns are still being investigated. Future research could explore how dopamine responses differ across individuals, how they are altered in psychiatric conditions, and whether interventions targeting specific brain circuits could reduce excessive avoidance behaviors.

The team also plans to explore how dopamine responses are shaped by experiences such as chronic stress, drug withdrawal, or persistent pain—conditions that involve altered learning and avoidance. By understanding how dopamine shapes behavior in the face of negative outcomes, scientists hope to better address mental health problems that disrupt people’s ability to function in everyday life.

The study, “Region-specific nucleus accumbens dopamine signals encode distinct aspects of avoidance learning,” was authored by Gabriela C. Lopez, Louis D. Van Camp, Ryan F. Kovaleski, Michael D. Schaid, Venus N. Sherathiya, Julia M. Cox, and Talia N. Lerner.

URL: https://www.psypost.org/neuroscientists-challenge-dopamine-detox-trend-with-evidence-from-avoidance-learning/

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DATE: May 23, 2025 at 02:00PM
SOURCE: PSYPOST.ORG

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TITLE: Non-right-handedness is more common across multiple mental health conditions

URL: https://www.psypost.org/non-right-handedness-is-more-common-across-multiple-mental-health-conditions/

People with mental or neurodevelopmental disorders are more likely to show non-right-handedness than those without these conditions, according to a second-order meta-analysis published in Psychological Bulletin.

Handedness—the tendency to prefer one hand over the other—is rooted in our biology and brain organization. Most people are right-handed, but left- and mixed-handed individuals comprise a significant minority. Handedness is shaped by both genetic and environmental factors, and emerges early in development, even prenatally. It is also associated with brain lateralization, especially in regions involved in language. Because some mental and neurodevelopmental disorders are also linked to altered brain asymmetry, researchers have suspected that handedness might reflect underlying neurocognitive differences relevant to these conditions.

Julian Packheiser and colleagues examined this possibility more systematically by conducting a second-order meta-analysis: essentially, a meta-analysis of meta-analyses.

The researchers first identified 10 relevant meta-analyses that examined conditions such as ADHD, autism, depression, dyslexia, dyscalculia, intellectual disability, PTSD, pedophilia, stuttering, and schizophrenia. Each meta-analysis included studies comparing individuals diagnosed with a given condition to healthy control groups, and provided data on whether participants were right-handed, left-handed, or mixed-handed.

The research team updated each of these existing meta-analyses by searching for and incorporating newly published studies, adding 33 additional datasets to the original 369, for a total of 402 datasets spanning over 202,000 individuals.

The final dataset encompassed a broad range of mental and neurodevelopmental disorders, and included detailed information about participant age, sex ratio, handedness classification methods, and geographical location of studies. Data were extracted and reanalyzed using a consistent statistical pipeline. Only studies with both clinical and control groups, clear handedness reporting, and no handedness-based participant selection were included. Key moderator variables were also coded, such as whether the disorder was neurodevelopmental, whether it involved language-related symptoms, and the typical age of onset.

Across all studies, individuals with mental or neurodevelopmental conditions were more likely to show atypical hand preferences, meaning they were either left-handed or mixed-handed, than healthy controls. The overall odds ratio indicated that people with these conditions were about 1.5 times more likely to be non-right-handed.

When looking specifically at left-handedness and mixed-handedness, both were significantly more common in clinical groups, with mixed-handedness showing the strongest association. However, these trends varied substantially depending on the disorder. Schizophrenia, autism spectrum disorder, and intellectual disability showed the most pronounced associations with atypical handedness, while conditions like depression and dyscalculia showed no significant differences compared to controls.

When the researchers explored potential moderating factors, several patterns emerged. Disorders that are classified as neurodevelopmental—such as ADHD, autism, dyslexia, dyscalculia, intellectual disability, and stuttering—showed significantly higher rates of non-right-handedness compared to non-neurodevelopmental disorders.

Additionally, conditions associated with language difficulties were more strongly linked to atypical handedness, supporting the idea that disruptions in brain asymmetry may affect both language and motor function. Among the non-neurodevelopmental conditions, those with an earlier average age of onset, such as schizophrenia and PTSD, also showed elevated rates of non-right-handedness. These patterns suggest that early brain development may play a key role in shaping both handedness and vulnerability to certain psychiatric conditions.

Taken together, the results reveal that handedness differences are not uniformly present across all mental health conditions, but instead appear to cluster in disorders with strong neurodevelopmental components or those that impact language processing and early brain development.

One limitation is that analyses relied solely on categorical measures of hand preference (i.e., right, left, or mixed), due to limited availability of continuous handedness measures. This may have constrained the sensitivity of some analyses.

The research, “Handedness in Mental and Neurodevelopmental Disorders: A Systematic Review and Second-Order Meta-Analysis,” was authored by Julian Packheiser, Jette Borawski, Gesa Berretz, Sarah Alina Merklein, Marietta Papadatou-Pastou, and Sebastian Ocklenburg.

URL: https://www.psypost.org/non-right-handedness-is-more-common-across-multiple-mental-health-conditions/

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DATE: May 23, 2025 at 12:00PM
SOURCE: PSYPOST.ORG

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TITLE: Withdrawal symptoms are common after stopping antidepressants

URL: https://www.psypost.org/withdrawal-symptoms-are-common-after-stopping-antidepressants/

A new study published in Molecular Psychiatry estimates that about 43% of people who stop taking antidepressants experience withdrawal symptoms. These symptoms typically appear within two weeks of stopping the medication and can range from mild to severe. The findings suggest that withdrawal effects are widespread and highlight the need for better guidance on how to discontinue antidepressants safely.

Antidepressants are some of the most widely prescribed medications for mental health conditions such as depression and anxiety. While they can be effective, many people remain on them for extended periods. In the United States, nearly half of antidepressant users have been taking them for over five years. In the United Kingdom, the majority have used them for more than two years. Despite this long-term use, withdrawal symptoms that can follow discontinuation are not fully understood. Previous reports have varied widely in estimating how common these symptoms are—ranging from as low as 3% to as high as 77%.

To address this uncertainty, researchers led by Mi-Mi Zhang and colleagues at Peking University conducted the most comprehensive analysis to date on antidepressant withdrawal symptoms. Their goal was to estimate how often these symptoms occur, what they typically look like, and what factors increase the risk of experiencing them. They also aimed to provide clearer evidence to guide clinicians and patients when it comes to tapering off these medications.

The researchers systematically reviewed six major medical databases and included 35 studies in their final analysis. These studies included randomized controlled trials, as well as observational and cross-sectional research. In total, the analysis covered data from tens of thousands of individuals who had stopped taking antidepressants. Some studies tracked patients in clinical settings, while others relied on self-reports from online surveys. Across these different types of studies, the researchers consistently found that withdrawal symptoms were common.

The pooled incidence of antidepressant withdrawal symptoms across all studies was 42.9%. Among randomized controlled trials, the rate was slightly higher at 44.4%. Symptoms typically emerged within two weeks after stopping the medication and were generally measured for less than four weeks. However, some long-term users reported that symptoms lasted for months or even years. For example, one online survey found that “brain zaps”—a sudden electrical shock-like sensation in the head—could persist for decades.

The severity of symptoms also varied. Most people experienced mild to moderate symptoms, especially after short-term use of 8 to 12 weeks. However, a significant minority reported severe or even very severe symptoms, especially those who had been on antidepressants for a longer time. In one study, nearly half of the participants who discontinued venlafaxine after 8 weeks experienced moderate or severe symptoms.

The types of withdrawal symptoms also depended somewhat on the class of antidepressant. For selective serotonin reuptake inhibitors (SSRIs), the most commonly reported symptoms included dizziness, increased dreaming or nightmares, irritability, and anxiety. For serotonin-norepinephrine reuptake inhibitors (SNRIs), neurological symptoms like dizziness were more common. Tricyclic antidepressants had the highest estimated withdrawal rate (around 60%), but were less frequently studied.

Although the study found that tapering the dose over time was associated with a lower incidence of withdrawal symptoms compared to abruptly stopping the medication (34.5% vs. 42.5%), the difference was not statistically significant. This may be due to the relatively short tapering periods used in most studies—typically just 2 to 4 weeks. Some experts argue that much longer tapering schedules may be needed, especially for people who have been on antidepressants for years.

Several risk factors were associated with an increased likelihood of experiencing withdrawal symptoms. These included being female, younger age, experiencing early side effects during treatment, higher doses, longer treatment durations, and abrupt cessation. There is also some evidence that genetic differences, such as variation in a serotonin receptor gene, may play a role.

Interestingly, the researchers found that psychological factors—such as expecting to feel worse after stopping the medication—were not the main drivers of withdrawal symptoms. In randomized controlled trials, the group that actually stopped taking the medication had much higher rates of symptoms than those who continued treatment, suggesting that the symptoms were not just caused by expectations.

Despite the robust findings, the study does have limitations. Most of the included studies followed patients for only a few weeks after discontinuation, which may underestimate the true duration and severity of symptoms. There was also substantial variation in how withdrawal symptoms were measured and defined, which may affect the accuracy of the estimates. The authors also noted the possibility of publication bias, meaning studies with higher rates of withdrawal symptoms might have been more likely to be published.

Another key limitation is that most of the studies focused on people who had taken antidepressants for relatively short periods—often less than three months. This is not representative of typical long-term users, who may be more prone to withdrawal symptoms and whose experiences may differ in important ways. The researchers emphasize the need for future studies that track withdrawal in long-term users over extended follow-up periods.

Despite these limitations, the study provides strong evidence that withdrawal symptoms are a common experience for people discontinuing antidepressants. The findings challenge the notion that stopping these medications is usually straightforward and stress the importance of patient education and individualized discontinuation plans.

The authors recommend that clinicians inform patients of the possibility of withdrawal symptoms when starting an antidepressant and monitor them closely during and after discontinuation. They also call for better research into long-term use and more refined tapering strategies, which could help reduce the risks associated with stopping antidepressants.

The study, “Incidence and risk factors of antidepressant withdrawal symptoms: a meta-analysis and systematic review,” was authored by Mi-Mi Zhang, Xuan Tan, Yong-Bo Zheng, Na Zeng, Zhe Li, Mark Abie Horowitz, Xue-Zhu Feng, Ke Wang, Zi-Yi Li, Wei-Li Zhu, Xinyu Zhou, Peng Xie, Xiujun Zhang, Yumei Wang, Jie Shi, Yan-Ping Bao, Lin Lu, and Su-Xia Li.

URL: https://www.psypost.org/withdrawal-symptoms-are-common-after-stopping-antidepressants/

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DATE: May 23, 2025 at 10:00AM
SOURCE: PSYPOST.ORG

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TITLE: Anxious attachment linked to depression spillover in romantic relationships, study finds

URL: https://www.psypost.org/anxious-attachment-linked-to-depression-spillover-in-romantic-relationships-study-finds/

A study from Germany has found that women with anxious attachment styles face a slightly elevated risk of depressive symptom spillover from their partners. In other words, when their partners reported higher levels of depressive symptoms, anxiously attached women were slightly more likely to experience increases in their own depressive symptoms compared to securely attached women. The study was published in Personal Relationships.

Depressive symptoms include persistent sadness, loss of interest or pleasure, fatigue, changes in appetite or sleep, and difficulty concentrating. While major depressive disorder is a common mental health diagnosis, many individuals experience depressive symptoms that do not meet the criteria for a clinical diagnosis.

These symptoms often do not remain isolated. In romantic relationships, one partner’s depressive symptoms can influence the other partner, potentially leading to increased symptoms over time. This phenomenon is referred to as spillover or crossover of depressive symptoms. However, because both partners are often exposed to similar external stressors, it is sometimes unclear whether such changes are due to true spillover or shared environmental influences affecting both individuals simultaneously.

Study author Preston C. Morgan and his colleagues sought to examine the extent to which a partner’s anxious attachment moderates the spillover of depressive symptoms over time in romantic relationships. Specifically, they wanted to determine whether men’s or women’s initial depressive symptoms could predict changes in their partner’s symptoms over a four-year period—and whether this effect was influenced by anxious attachment. Anxious attachment is a relational style characterized by a heightened fear of abandonment, increased sensitivity to rejection, and a strong need for closeness and reassurance.

The researchers analyzed data from the German Panel Analysis of Intimate Relationships and Family Dynamics (Pairfam), using five waves of data collected between 2010 and 2014.

The final sample included 1,179 heterosexual couples who remained together throughout the study period. At the start of the study, the average age was approximately 36 for men and 33 for women, and 72% of the couples were married. Participants completed validated assessments of depressive symptoms and anxious attachment.

The results showed that participants’ initial levels of depressive symptoms were not significantly associated with changes in their partners’ depressive symptoms across the four-year period. However, women’s anxious attachment significantly moderated this association. In particular, women with higher levels of anxious attachment were slightly more likely to experience increases in their own depressive symptoms when their male partners had elevated depressive symptoms at the start of the study.

“In general, depressive symptoms in one partner seem to be at least partially transferrable to the other romantic partner. This depressive symptom spillover seems to occur at the same time point, but men’s and women’s initial depressive symptoms were not associated with changes in their partner’s depressive symptom trajectories—limiting the spillover effect. However, this long-term spillover effect may occur in one context. Specifically, women who are more anxiously attached—seeking increased reassurance—are at an even higher risk for depressive symptom spillover within their romantic relationships,” the study authors concluded.

The study sheds light on the depressive symptom spillover effect within couples. However, it should be noted that the mean depression level of study participants was low and that these were not clinically depressed individuals. This may have limited the magnitude of detected spillover effects. Furthermore, the study sample was limited to couples who remained together during the study period. Results on other categories of individuals may differ.

The paper, “Depressive symptoms spillover between romantic partners partially explained by anxious attachment,” was authored by Preston C. Morgan, Jared A. Durtschi, and Salena King.

URL: https://www.psypost.org/anxious-attachment-linked-to-depression-spillover-in-romantic-relationships-study-finds/

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DATE: May 23, 2025 at 08:00AM
SOURCE: PSYPOST.ORG

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TITLE: Scientists find 16 new Alzheimer’s-linked genes using multi-ancestry genome data

URL: https://www.psypost.org/scientists-find-16-new-alzheimers-linked-genes-using-multi-ancestry-genome-data/

A new study published in Alzheimer’s & Dementia has identified 16 novel genetic regions associated with Alzheimer’s disease by analyzing whole genome sequencing data from a large, ethnically diverse group of individuals. The findings emphasize the importance of including underrepresented populations in genetic research and point to new biological pathways that may play a role in the development of the disease.

Alzheimer’s disease is the most common form of dementia, affecting millions of people around the world. While the disease is known to have a strong genetic component, most studies of its genetic basis have focused on individuals of European ancestry. This limits understanding of the disease’s full genetic architecture and may leave important variants undiscovered. The researchers behind this new study sought to address that gap by analyzing genomic data from over 430,000 individuals of diverse backgrounds, including participants of African, Hispanic/Latino, and other ancestries.

“Alzheimer’s disease is a complex disease with contributions from both genetics and environment,” said Dmitry Prokopenko of the Genetics and Aging Research Unit and the McCance Center for Brain Health at Massachusetts General Hospital. “Most of the previous genome-wide association studies were focused on cohorts with subjects of European descent. Here we have studied diverse cohorts and biobanks with about 50% of non-European descent.”

The team drew on data from four major sources: the National Institute on Aging Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS), the National Institute of Mental Health (NIMH), the UK Biobank, and the All of Us Research Program. The combined dataset included more than 49,000 Alzheimer’s cases—12,074 with a clinical diagnosis and 37,075 defined by a family history of the disease—and over 383,000 controls. Notably, nearly half of the participants from the NIAGADS and All of Us cohorts were of non-European ancestry, providing a much-needed level of diversity.

To identify genetic variants linked to Alzheimer’s, the researchers conducted a genome-wide association study, a method that scans the genome for variants more common in people with the disease than in those without. For clinical Alzheimer’s diagnoses, they uncovered 14 new genetic loci, five of which were common variants and nine of which were rare. These loci were located near or within genes that play roles in brain function, immune response, and cellular signaling.

Among the newly identified common variants were those near the genes FBN2, SLC27A6, DYM, KCNG1, and TIAM1. These genes are involved in processes such as neural connectivity, fatty acid metabolism, and synaptic signaling. For example, FBN2 and SLC27A6 were found to be more active in neurons of individuals with Alzheimer’s pathology, suggesting they may contribute to disease development or progression. KCNG1, a gene related to potassium channels, showed altered expression in both neurons and astrocytes, hinting at a potential role in brain electrical signaling.

The study also identified nine rare variants in genes such as VWA5B1, PDE4D, and NEO1, among others. These rare variants may have strong effects on disease risk, even though they are present in only a small portion of the population. Identifying such variants is especially important for understanding Alzheimer’s in populations that have been historically underrepresented in genetic studies.

In addition to studying people with confirmed clinical diagnoses, the researchers also examined a group of individuals categorized as having “Alzheimer’s disease by proxy”—that is, people with a family history of the disease but no personal diagnosis. Using data from the UK Biobank and All of Us, they conducted a similar genetic analysis and found two new rare loci associated with increased Alzheimer’s risk. These were located near the genes RPL23/LASP1 and CEBPA, both of which are involved in cellular functions that may influence brain health. CEBPA, for instance, plays a role in regulating immune responses in the brain.

The team then compared the findings from the two analyses—clinical Alzheimer’s cases and Alzheimer’s-by-proxy cases. While some overlap existed, most of the new loci identified in one dataset did not replicate in the other. This suggests that the two approaches may capture different aspects of the disease’s genetic architecture, particularly across populations of varying ancestry.

Importantly, the researchers assessed whether the newly discovered genetic regions were located near genes with altered activity in the brains of people with Alzheimer’s. They used previously published single-cell data that mapped gene expression in various brain cell types, such as neurons and astrocytes. Many of the newly identified genes, including DYM, TIAM1, and PDE4D, were indeed differentially expressed in individuals with cognitive impairment and hallmark Alzheimer’s pathology.

These findings offer promising leads for future research into the mechanisms of Alzheimer’s disease. By revealing new genetic associations and linking them to biological changes in the brain, the study helps lay the groundwork for new strategies to predict, prevent, and treat the disease. It also underscores the importance of including participants from a wide range of genetic backgrounds in research.

Despite its strengths, the study has some limitations. The definition of Alzheimer’s-by-proxy relies on self-reported family history, which may introduce errors or inconsistencies, especially in more diverse populations where diagnosis rates may vary due to disparities in healthcare access. Additionally, many of the variants identified in the more diverse All of Us dataset did not replicate in the clinical dataset, raising the possibility of false positives or ancestry-specific effects that require further investigation.

Future research should focus on validating these newly identified loci in independent cohorts and exploring how they influence brain biology. Functional experiments, including laboratory studies of gene expression and protein function, will be necessary to determine the roles these variants play in Alzheimer’s disease.

“Our paper underscores the importance of using diverse cohorts with well-defined phenotypes for discovery and validation,” Prokopenko told PsyPost. “Our study can help discover new precision medicine approaches in diverse populations. Such genetic studies help scientists to discover new biological pathways and disease mechanisms. However, additional studies are needed to fully replicate these novel findings. As next steps, we plan to use gene-based testing to combine signals from multiple rare variants within a gene or functional elements to test for disease association.”

The study, “Identification of 16 novel Alzheimer’s disease loci using multi-ancestry meta-analyses,” was authored by Julian Daniel Sunday Willett, Mohammad Waqas, Younjung Choi, Tiffany Ngai, Kristina Mullin, Rudolph E. Tanzi, and Dmitry Prokopenko.

URL: https://www.psypost.org/scientists-find-16-new-alzheimers-linked-genes-using-multi-ancestry-genome-data/

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