Designing Smarter ALS Studies: Best Practices with JAX Mouse Models

Developing therapies for amyotrophic lateral sclerosis (ALS) is difficult. The disease destroys motor neurons, causing progressive weakness, paralysis, and eventually death, and its causes vary widely. About 10% of cases are familial, linked to mutations in more than 40 genes, while the rest are sporadic and arise from a mix of genetic, environmental, and molecular factors. That complexity means small decisions in preclinical study design can shape the results.

This guide covers how to choose the right model, select meaningful readouts, and avoid common experimental pitfalls.

What Are Common Challenges in ALS Research?

The first thing to consider when designing an ALS study is that ALS is driven by a diverse set of distinct disease mechanisms, including protein aggregation, RNA processing defects, neuroinflammation, oxidative stress, and neuromuscular junction dysfunction. No single model can answer every scientific question, so it is important to select a model whose disease mechanism fits your specific question (we cover this in more detail in the next section).

You should also consider variables such as biomarker selection, treatment timing, and study power, all of which can influence results. Many past examples have shown that poorly designed studies can generate misleading efficacy data and contribute to failed clinical translation.

Which In Vivo Mouse Model Should I Choose?

A successful ALS study begins with selecting a model that best aligns with the biology of the therapeutic being tested. Each model should be evaluated on its ability to reproduce key clinical features of ALS and recapitulate disease mechanisms relevant to patients. Of the many genes associated with familial ALS, four account for the majority of cases: SOD1, TARDBP (TDP-43), FUS, and C9orf72. JAX provides validated models covering each of these key genetic variants, so selecting one with a variant in one of these genes is a good place to start.

SOD1 Models

Mutations in superoxide dismutase 1 (SOD1) can cause a toxic gain of function, leading to protein misfolding and aggregation, oxidative stress, and mitochondrial dysfunction.

Our SOD1-G93A mouse is one of the most widely used ALS models. These mice develop progressive weakness, muscle atrophy, neuroinflammation, and reduced survival, making them valuable for studying disease progression and therapeutic efficacy. Overt disease signs typically appear at around 80–90 days of age, providing a well-characterized framework for intervention studies.

TDP-43 Models

Mutations in the TARDBP gene cause the TDP-43 protein to leave the nucleus and form aggregates in the cytoplasm and neurites. This mislocalization isn’t limited to TARDBP carriers: TDP-43 pathology appears in many ALS cases, including sporadic ones, which makes it one of the most broadly relevant targets in the field.

The JAX TDP-43 Q331K model shows progressive motor neuron dysfunction and gradual loss of muscle strength and neuromuscular function. It’s a strong choice for testing therapies aimed at TDP-43 mechanisms, such as reducing aggregation or restoring normal nuclear localization.

C9orf72 Models

A hexanucleotide repeat expansion in the C9orf72 gene is a common genetic cause of ALS, accounting for roughly 45% of familial cases. The expansion drives neurotoxicity through both RNA- and protein-mediated mechanisms, so C9orf72 models are well suited to researchers studying RNA metabolism, neuroinflammation, protein aggregation, or repeat-expansion pathology more broadly.

The JAX Tg(C9orf72_3) line 112 carries several tandem copies of the C9orf72_3 transgene. By 3 months of age, these mice show RNA foci and poly(GP) dipeptides in most neuronal populations of the brain.

Besides the Model, Is There Anything Else I Should Consider?

Beyond choosing a model that recapitulates the disease mechanisms relevant to your study, you should also carefully choose your biomarkers, dose timing, and study size. Each is covered below.

Selecting Meaningful Biomarkers

Biomarkers are the measurable signals of disease onset, progression, and treatment response in ALS mouse models, and choosing them well is central to any robust efficacy study. Poorly chosen biomarkers can undermine an otherwise sound design, while those that shift early in the disease course offer a clearer, earlier view of whether a therapy is working.

Common ALS biomarkers include:

JAX research has shown that NfL and electrophysiological measures often detect disease progression before body-weight loss becomes apparent, giving an earlier read on therapeutic activity.

Getting Dose Timing Right

Dose timing is another key factor in well-designed ALS research. Starting treatment too early may overestimate efficacy, because the therapy prevents pathology before it has a chance to develop. Starting too late may underestimate efficacy, because substantial neurodegeneration has already occurred.

At JAX, we recommend matching treatment before the onset of overt disease symptoms, allowing researchers to evaluate therapeutic effects during the early stages of disease progression.

Partner with JAX to Accelerate Your ALS Research

High-quality ALS studies depend on thoughtful model selection, meaningful biomarkers and endpoints, rigorous execution, and a deep understanding of disease biology. JAX brings decades of expertise in mouse genetics, along with validated ALS models, natural history datasets, advanced biomarker capabilities, and comprehensive preclinical services, to help researchers generate robust, translatable data.

Whether you need a specific ALS model, guidance on study design, or full-service preclinical support, JAX has the expertise and resources to move your research forward.

Learn more about JAX models and preclinical services for neuroscience:

Models for Neuroscience Research

Preclinical Services for ALS

Designing Smarter ALS Studies: Best Practices with JAX Mouse Models