ADRD Biomarker Heterogeneity: The Zetterberg Framework

ADRD Biomarker Heterogeneity: The Zetterberg Framework

Overview

At [AD/PD 2026](/conferences/adpd-2026), Henrik Zetterberg (University of Gothenburg, Sahlgrenska Academy) delivered a keynote framing disease heterogeneity as the central, unresolved challenge in [Alzheimer Disease and Related Dementias (ADRD) biomarker research](/biomarkers/blood-based-biomarkers-neurodegeneration)[@zetterberg2026]. His core message: neurodegeneration is not a single disease but a spectrum of distinct biological processes that manifest clinically as similar syndromes. Effective biomarkers must account for this diversity at genetic, molecular, cellular, and clinical levels.

Zetterberg's framework builds on a decade of fluid biomarker work from his group and others, and aligns with emerging consensus that the field must move beyond simple amyloid-positive vs. amyloid-negative dichotomies toward multidimensional, patient-specific biological profiles.

The Heterogeneity Problem

Why Standard Biomarkers Fail

Traditional biomarker approaches assume a relatively homogeneous disease process: amyloid accumulation drives tau pathology, which drives neurodegeneration, which drives cognitive decline. This linear cascade model underpins the [amyloid cascade hypothesis](/mechanisms/amyloid-cascade-hypothesis)[@hardy1992][@karran2011].

However, multiple independent cohorts have demonstrated that:

ADRD Biomarker Heterogeneity: The Zetterberg Framework

Overview

At [AD/PD 2026](/conferences/adpd-2026), Henrik Zetterberg (University of Gothenburg, Sahlgrenska Academy) delivered a keynote framing disease heterogeneity as the central, unresolved challenge in [Alzheimer Disease and Related Dementias (ADRD) biomarker research](/biomarkers/blood-based-biomarkers-neurodegeneration)[@zetterberg2026]. His core message: neurodegeneration is not a single disease but a spectrum of distinct biological processes that manifest clinically as similar syndromes. Effective biomarkers must account for this diversity at genetic, molecular, cellular, and clinical levels.

Zetterberg's framework builds on a decade of fluid biomarker work from his group and others, and aligns with emerging consensus that the field must move beyond simple amyloid-positive vs. amyloid-negative dichotomies toward multidimensional, patient-specific biological profiles.

The Heterogeneity Problem

Why Standard Biomarkers Fail

Traditional biomarker approaches assume a relatively homogeneous disease process: amyloid accumulation drives tau pathology, which drives neurodegeneration, which drives cognitive decline. This linear cascade model underpins the [amyloid cascade hypothesis](/mechanisms/amyloid-cascade-hypothesis)[@hardy1992][@karran2011].

However, multiple independent cohorts have demonstrated that:

• Not all amyloid-positive individuals progress at the same rate — some remain cognitively stable for years
• Non-amyloid pathologies (alpha-synuclein, TDP-43, vascular injury, neuroinflammation) co-occur in many patients, driving clinical outcomes independently of amyloid
• Genetic heterogeneity — APOE ε4 carriers, LRRK2 G2019S carriers, and sporadic cases show distinct biomarker trajectories
• Demographic heterogeneity — Age, sex, education, and vascular risk profiles alter both biomarker levels and clinical expression

Evidence for Multiple Parallel Pathways

Key evidence for heterogeneity in ADRD comes from several converging lines:

The Zetterberg Heterogeneity Framework

Zetterberg's framework identifies four layers of heterogeneity that biomarker development must address:

Layer 1: Genetic Heterogeneity

ADRD risk is driven by hundreds of genetic variants with varying effect sizes. The framework distinguishes:

• Amyloid-directed genetics: APOE ε4 (strong risk), CLU, PICALM, BIN1
• Immune/microglial genetics: TREM2, PLCG2, INPP5D, CSF1R
• Synucleinopathy genetics: LRRK2 G2019S, SNCA multiplications, GBA variants
• Tau/FTD genetics: MAPT, GRN, C9orf72
• Polygenic risk scores (PRS): Composite scores aggregate hundreds of variants, but different PRS components predict different biomarker trajectories

Layer 2: Molecular Heterogeneity

Multiple distinct proteinopathies can drive neurodegeneration independently or in combination:

• Amyloid-beta (Aβ) — plaques, soluble oligomers
• Phosphorylated tau (p-tau181, p-tau217, p-tau231) — spreading pathology
• Alpha-synuclein (α-syn) — Lewy bodies, neuronal inclusions
• TDP-43 (TAR DNA-binding protein 43) — limbic-predominant age-related TDP-43 encephalopathy (LATE)
• Vascular pathology — white matter lesions, microinfarcts
• Neuroinflammation — elevated GFAP, IL-6, sTREM2

Layer 3: Cellular Heterogeneity

Even within a single molecular pathology, different cell types respond differently:

• Microglial states: homeostatic (TMEM119+, P2RY12+) → disease-associated (DAM/MGND, IRM), transitioning through intermediate states[@zetterberg2026]
• Astrocyte reactivity: A1 (neurotoxic) vs. A2 (neuroprotective) phenotypes
• Synaptic loss: Pre-synaptic (NPTX1, NPTXR) vs. post-synaptic (GAP-43) markers[@schweigert2024]

Layer 4: Clinical Heterogeneity

The same molecular pathology produces different clinical syndromes:

• Amnestic vs. non-amnestic presentation in Alzheimer's
• Parkinsonism vs. dementia-first in synucleinopathies
• Rapid vs. slow progression even with similar biomarker profiles
• Atypical variants: posterior cortical atrophy, logopenic aphasia, behavioral variant FTD

Implications for Fluid Biomarker Development

Blood-Based Biomarker Strategies

The framework has direct implications for the ongoing development of blood-based biomarkers:

Clinical Trial Design

The heterogeneity framework reshapes clinical trial design:

• Enrichment strategies: Selecting patients based on multiple biomarkers (e.g., amyloid-positive + specific tau strain + absence of α-synuclein co-pathology) rather than single criterion
• Outcome measure selection: Cognitive endpoints may not capture drug effects if the treated pathology is not the primary driver of clinical decline in that patient subset
• Stratified medicine: Ultimately, ADRD drug development may need to follow oncology's model of molecularly defined subtypes with targeted therapies

Research Priorities

Based on this framework, Zetterberg outlined key research priorities for the field:

Cross-Links

• [Blood-based biomarkers for neurodegeneration](/biomarkers/blood-based-biomarkers-neurodegeneration) — General overview of fluid biomarkers
• [Plasma p-tau217 biomarker](/biomarkers/plasma-ptau217-alzheimers) — Key tau biomarker in Zetterberg's framework
• [Alpha-synuclein PET imaging advances](/biomarkers/alpha-synuclein-pet-imaging-advances) — Synuclein-specific imaging
• [Amyloid cascade hypothesis](/mechanisms/amyloid-cascade-hypothesis) — The linear model this framework challenges
• [Neuroinflammation biomarkers](/biomarkers/neuroinflammation-biomarkers) — Glial activation markers
• [Henrik Zetterberg researcher page](/researchers/henrik-zetterberg) — Lead researcher in ADRD biomarkers

References